Avatar facial expression representation in multidimensional space

ABSTRACT

Examples of the disclosed systems and methods may provide for improved and more realistic rendering of virtual characters and a more realistic interaction between a user and virtual characters. For example, the systems and methods describe techniques for mathematically generating a map used for animating facial expressions in a multidimensional animation blendspace. As another example, the systems and methods describe a transition system for dynamically transitioning facial expressions across a face of the virtual character. As another example, realistic physical movements can be added to a virtual character&#39;s facial expressions to provide interactivity with other virtual characters.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. patent applicationSer. No. 16/359,851, filed Mar. 20, 2019, entitled AVATAR FACIALEXPRESSION REPRESENTATION IN MULTIDIMENSIONAL SPACE, which claims thebenefit of priority to U.S. Patent Application No. 62/661,522, filedApr. 23, 2018, entitled AVATAR FACIAL EXPRESSION REPRESENTATION INMULTIDIMENSIONAL SPACE, which is hereby incorporated by reference hereinin its entirety.

FIELD

The present disclosure relates to animations of virtual characters andmore particularly to control facial expressions of the virtualcharacters.

BACKGROUND

A virtual character may be a virtual representation of a real orfictional person (or creature or personified object) in a virtualenvironment. For example, during a telepresence session in which twousers are interacting with each other in a mixed reality environment, aviewer can perceive a virtual character of another user in the viewer'senvironment and thereby create a tangible sense of the other user'spresence in the viewer's environment. The virtual character can alsoprovide a way for users to interact with each other and do thingstogether in a shared virtual environment. For example, a studentattending an online class can perceive and interact with virtualcharacters representing other students or the teacher in a virtualclassroom. As another example, a user playing a video game may view andinteract with virtual characters of other players in the game.

SUMMARY

Examples of the disclosed systems and methods may provide for improvedand more realistic rendering of virtual characters and a more realisticinteraction between a user and virtual characters. For example, thesystems and methods describe techniques for mathematically generating amap for representing facial expressions of a virtual character in amultidimensional animation blendspace. The systems and methods canutilize the map to more realistically render virtual characters. Asanother example, the systems and methods provide for dynamicallytransitioning facial expressions across a face of the virtual character.As another example, realistic physical movements can be added to avirtual character's facial expressions to provide realism andinteractivity with other virtual characters.

Embodiments of these system and methods are particularly applicable toreal-time rendering in a mixed, virtual, or augmented realityenvironment. Other embodiments of these systems and methods can be usedin gaming, movies, and visual effects (VFx).

Although certain embodiments and examples are disclosed herein,inventive subject matter extends beyond the examples in the specificallydisclosed embodiments to other alternative embodiments and/or uses, andto modifications and equivalents thereof.

BRIEF DESCRIPTION OF THE DRAWINGS

Details of one or more implementations of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages will becomeapparent from the description, the drawings, and the claims.

FIG. 1 depicts an illustration of a mixed reality scenario with certainvirtual reality objects, and certain physical objects viewed by aperson.

FIG. 2 schematically illustrates an example of a wearable system.

FIG. 3 schematically illustrates example components of a wearablesystem.

FIG. 4 schematically illustrates an example of a waveguide stack of awearable device for outputting image information to a user.

FIG. 5 is a process flow diagram of an example of a method forinteracting with a virtual user interface.

FIG. 6A is a block diagram of another example of a wearable system whichcan comprise an avatar processing and rendering system.

FIG. 6B illustrates example components of an avatar processing andrendering system.

FIG. 7 is a block diagram of an example of a wearable system includingvarious inputs into the wearable system.

FIG. 8 is a process flow diagram of an example of a method of renderingvirtual content in relation to recognized objects.

FIG. 9A schematically illustrates an overall system view depictingmultiple wearable systems interacting with each other.

FIG. 9B illustrates an example telepresence session.

FIG. 10 illustrates an example of an avatar as perceived by a user of awearable system.

FIG. 11 illustrates an example of sliders associated with a facial rig.

FIG. 12A illustrates examples of face vectors representing facialexpressions.

FIG. 12B illustrates an example of a map of expressions.

FIG. 12C illustrates examples of face vectors and a triangular animationblendspace on the map of expressions of FIG. 12B.

FIG. 12D illustrates another example of a map of expressions.

FIG. 13 illustrates an example process of generating a map of facialexpressions for an animation blendspace.

FIG. 14A illustrates an example of transitions of expressions for avirtual character where the whole face changes from one state to anotherat the same time.

FIGS. 14B and 14C illustrate an example of a swept transition mechanismthat transitions expressions in different facial regions at differenttimes.

FIG. 15 illustrates an example process for transitioning facialexpressions.

FIG. 16A illustrates an example of face vectors for a transition betweena neutral expression and a shocked expression. The component values ofthe face vectors are sometimes referred to as sliders.

FIG. 16B illustrates examples of graphs associated with adding tunablecontrols to face sliders.

FIG. 17 illustrates an example of changes to face sliders at differentpoints in time where both the tunable control system and the swepttransition mechanism are implemented.

FIG. 18 illustrates an example process of animating a virtual characterwhich incorporates realistic physical movements.

FIG. 19 illustrates an example computing device for implementing varioustechniques associated with animating or rendering a virtual character.

Throughout the drawings, reference numbers may be re-used to indicatecorrespondence between referenced elements. The drawings are provided toillustrate example embodiments described herein and are not intended tolimit the scope of the disclosure.

DETAILED DESCRIPTION Overview

A virtual character can appear in a virtual application to provideinteractive user experiences. For example, a virtual character may bepart of an augmented reality, virtual reality, or mixed reality(AR/VR/MR) environment, a game application, a movie, or other visualcontent. A virtual character can be an avatar, or virtual objects. Thevirtual character can be animated with facial and emotional expressionsto provide a realistic user experience. The controls for theseexpressions may be driven by artificial intelligence. For example, thevirtual character may be pre-programmed to show an excited expressionwhen a user passes a level in a virtual game. As another example, thevirtual character may have a look of fear every time the virtualcharacter sees a spider. The expressions can also be real-time driven,e.g., based on a corresponding user's interaction. As an example, when auser of an AR/VR/MR system smiles, the user's avatar can also smile inthe virtual environment so that other AR/VR/MR users can see that theuser is smiling. As will further be described with reference to FIGS. 2and 4, the user's expressions can be determined based on data acquiredby an outward-facing imaging system, an inward-facing imaging system, ora video or a camera in a room where the user is utilizing the AR/VR/MRdevice. As yet another example, a user can control the facialexpressions of a virtual avatar remotely, e.g., via a map of facialexpressions (described with reference to FIGS. 12B and 12C). In thisexample, the facial expressions of the virtual avatar do not have tomatch those of the user. For example, the user can talk to anotherperson in the environment or have a neutral expression whereas the usercan control the virtual avatar to look happy via the map.

Facial expressions of a virtual character can be animated usingcombinations of blendshapes. Blendshapes can be combined using a facevector, where each value in the vector represents a setting for a singleblendshape. A blendshape setting can denote a magnitude (or weight) withwhich to incorporate that blendshape. Each blendshape can add anadditional level of dimensionality to the virtual character's face,which can provide another way for a user to further manipulatedeformations of the virtual character's facial mesh. Accordingly, eachblendshape may be considered a parameter used to animate the virtualcharacter.

For example, in some facial rigs, a face vector can be defined as a setof numbers (e.g., components) in a multidimensional space of over onehundred dimensions (e.g., 137 dimensions in some examples). The valuefor each component can be, e.g., a Boolean value, an integer, or a realnumber defined over a range of values (e.g., 0 to 1, or −1 to +1). Ifeach component of the face vector were discretized to have, say, 10possible values, the total number of possible facial expressions wouldbe 10¹³⁷, in the above example, which is far greater than the number ofparticles that exist in the observable universe. Given such an enormousvolume of multidimensional space in which facial expressions can begenerated and rendered, the disclosed systems and methods can utilize aset of rules that are computationally implemented to dynamically animatea virtual character and to dynamically transition between differentfacial expressions.

To configure the visual effects associated with the facial expressions,the animation system can use a map which comprises two-dimensional (2D)projections of facial expressions. The map may be in the shape of awheel (e.g., similar to the map 1250 shown in FIG. 12B) or a morerectangular arrangement (e.g., similar to the map 1250 shown in FIG.12D). This map can serve as an interface to help an animator toconfigure animations more intuitively, because the animator is able tosee a chosen expression visually instead of a string of numbers andvariables in the face vector. In some situations, the map can also beused as a way for a person (e.g., a user of an AR/VR/MR device) tomanually control the facial expressions of an avatar (as describedabove). For example, the person can control the facial expression of thevirtual avatar using the map remotely even though the person is notperforming that particular expression in the real world.

An AR/VR/MR system can utilize the map to dynamically transition betweendifferent expressions of the avatar by generating and following atrajectory in the map between, e.g., an initial expression (e.g., aneutral expression) and a final expression (e.g., a smile). During thistransition, if some event were to cause the facial expression to changefrom the final expression (e.g., rather than transitioning to a smile,the avatar instead is to transition to a look of surprise), the systemcan dynamically alter the trajectory towards the new final expression(e.g., the look of surprise) in a natural and realistic manner.

Because numerous facial expressions can be animated for a virtualcharacter, it can be infeasible to project all possible facialexpressions onto the map (e.g., as noted above, the number of facialexpressions in a multidimensional facial space can greatly exceed thenumber of particles in the observable universe). Thus, a relativelysmall subset of possible facial expressions (or emotions) may beprojected onto the map and created with defined values of the facevector. The other expressions can be derived from the vectors associatedwith facial expressions in the subset of possible facial expressions,for example, by generating linear combinations of the vectors associatedwith the map.

However, if two arbitrary face vectors are combined, the resultingfacial expression may look odd and can break the realism of the virtualcharacter. For example, the avatar may look robotic cycling betweendifferent expressions rather than like a real person in whichexpressions smoothly change.

To reduce the likelihood of incorrect blending of facial expressions,the map can be generated such that positions of a relatively smallnumber (e.g., three) of closest expressions (used for generating theblended expression) on the map can be optimized. For example, thetechnique described herein can mathematically derive the layout of themap by creating an expression specific delta vector that represents anincrement (e.g., a delta) between a reference expression and the desiredexpression. In some embodiments, the reference expression corresponds toa neutral expression of the face. The delta vector can be calculated bysubtracting the vector values for the neutral expression from the vectorvalues of the desired expression (which will be projected onto the map).This permits the facial expression to be represented as a change (e.g.,the delta vector) relative to the neutral expression. Thus, the neutralexpression can serve as an origin at a given location (e.g., the center,top, bottom, or other locations) on the map, and the facial expressionscan be arrayed around this origin based on the geometric relationshipamong the delta vectors corresponding to these expressions (e.g.,lengths of the delta vectors and angular relationships between the deltavectors).

The relationships between the expressions can be determined based onmathematical operations applied to the facial vectors corresponding tovarious expressions. For example, the relationships can indicate whetherthe expressions are relatively similar to each other (e.g., surprisedand shocked, or displeased and disgusted) or more opposite to each other(e.g., displeased versus shocked). As an example, with reference to FIG.12A, the eye brows move up for the shocked expression whereas the eyebrows move slightly down for the displeased expression. As anotherexample, the jaw moves for the shocked expression but there is no jawmovement for the displeased expression. For two similar expressionsdispleased and disgusted, the movements of eye brows, eyes, and lipcorner are in the same direction but the magnitudes of the movements aredifferent. For example, the eye brows move down and the eyes opened upfor the displeased and disgusted expressions.

In some embodiments, the mathematical dot product operation can beapplied to the facial vectors or the expression specific delta vectorsto determine the relationships between the facial expressions. In someembodiments, the reference (e.g., neutral) expression may be placed inthe center of the map to allow the blending to have a common neutralexpression at a central location. The distance between an expression andthe neutral expression can be calculated based on the length of theexpression specific delta vector (e.g., the Euclidean or L2-norm of thevector).

In addition to or as an alternative to reducing the likelihood ofincorrect blending, the technique can advantageously create realisticintermediate expressions (e.g., which may be in-between or near twofacial expression vectors) for transitions between two expressions,because the expressions may be multiples of each other in terms ofintensity in each direction of the map (e.g., a happy expression is inthe same general direction as an ecstatic expression on the map). Thetransition between two expressions on the map can be along an expressionchange trajectory. For example, with reference to FIG. 12B, thetransition from disdained to terror can be along an expression changetrajectory which starts at the disdained expression and moves to worry,fear, and subsequently ends at the terror expression. The trajectory canbe automatically determined, for example, based on the relationships ofthe two expressions, the layout of the map, and so forth. By generatinga trajectory in the map between an initial expression and a finalexpression (which can dynamically be updated), the techniques describedherein may avoid a robotic or abrupt change of expression for the avatarand may produce a more realistic looking avatar. As will further bedescribed with reference to FIG. 12B, in some situations, a user of awearable system can also control the emotion change trajectory. Forexample, the user may interact with a visual representation of the mapon a virtual user interface and draw a trajectory comprising severalexpressions during the transition from an initial expression to an endexpression. For example, a user may draw a trajectory from the distainedexpression to the terror expression. This user drawn trajectory may gothrough exertion, to fear, and then to terror which may be in contrastwith the earlier example where the distained expression is transitionedto the terror expression via the worry and fear expressions.

Because the virtual character may be real time driven (e.g., in anAR/VR/MR environment, or via a remote computing device), a virtualcharacter's expression can change, in real time, from a first expressionto a second expression. The change from the first expression to thesecond expression can occur along the expression change trajectory.Thus, the first or the second expression can be an intermediaryexpression in the expression change trajectory. For example, theexpression change trajectory can include worried, fear, and terror, andthe virtual character's expression can change from worried to fear andthen to terror.

Traditional pre-rendered animation usually pre-selects two expressions—astart expression and end expression—and then blends the two fortransitioning. However, the transition in this method is pre-renderedanimation. The pre-rendered animation generally needs to be rendered inentirety before transitioning to a third expression, which may notreflect the actual change in expression desired for the avatar. Thus,pre-rendered transitions can look unnatural, robotic, or delayed.

To provide a less rigid transition and to provide a seamless flow from afirst expression to a second expression at any point in time, theanimation system for a virtual character can provide dynamic transitionsbetween expressions and allow expressions to sweep across the face,which is more realistic. For example, to go from a worried expression toa happy expression, the system can start at the chin and sweep up, wherea worried mouth turns into a smile followed by worried eyes turning intosmiling eyes, or the system could start at the forehead and sweep downwith the eyes changing from worried to smiling eyes then the mouthchanging from worried to smiling afterwards.

This transition system can specify parameters including a startingfacial expression, an ending facial expression, and a sweep direction(or sweep speed) for each point in time. With reference to FIG. 14A, thesweep direction can indicate a direction of change among the variousparts of the face during the transition from one facial expression tothe next. As one example, the transition from the happy expression tothe sad expression may follow a downward direction such that the controlvalues of the eyes are changed from those associated with happy to thoseassociated sad, and then the control values of the mouth is changed fromthose associated with happy to those associated sad. By employing thesweep direction for changing facial expressions, the animation systemthus may sweep from the starting facial expression to the ending facialexpression in a realistic and natural manner and over a realistic andnatural time frame, thereby avoiding robot-like transitions betweenfacial expressions. This technique can allow for transitions from anystarting point to any ending point and from any direction or at anytransition speed. The speed of the sweep (or the sweep direction) canalso be randomized for every play-through (associated with a transition)so that the avatar performs these transitions can appear slightlydifferently each time, which again mimics real-person behavior andappears less robotic and pre-programmed.

Realistic physical movements may be incorporated into animations ofvirtual characters to add realism to the transition. Advantageously, toenable realistic physical movements, the control system of the virtualcharacter can incorporate physical movements into the variables of theface vector directly without needing to implement a separatephysics-based program, which can be computationally challenging toexecute in real time. For example, in some embodiments of the controlsystem, tunable springs can be added to the control values in the facevector to provide a natural cyclic motion on certain regions of the face(e.g., the avatar's cheek may bounce when suddenly having a big smile).

Accordingly, embodiments of the disclosed systems and techniques can beused to quickly and automatically (or with limited or reduced humanintervention) generate facial expressions and transitions between facialexpressions for virtual avatars. For example, the avatar advantageouslycan be rendered so as to reduce the likelihood of entering the so-calleduncanny valley, which represents a dip in human emotional response to anavatar that is almost, but not quite, human in its appearance ormovements.

Although the examples described herein may use a human-shaped virtualavatar to illustrate various aspects of rendering by the control system,similar techniques can also be applicable to the animation of othertypes of virtual characters, such as, e.g., animals, fictitiouscreatures, objects, etc.

Examples of 3D Display of a Wearable System

Modern computing and display technologies have facilitated thedevelopment of systems for so called “virtual reality,” “augmentedreality,” and “mixed reality” experiences, wherein digitally reproducedimages are presented to a user in a manner such that they seem to be, ormay be perceived as, real. A virtual reality (VR) scenario typicallyinvolves presentation of computer-generated virtual image informationwithout transparency to other actual real-world visual input. Anaugmented reality (AR) scenario typically involves presentation ofvirtual image information as an augmentation to visualization of theactual world around the user. Mixed reality (MR) is a type of augmentedreality in which physical and virtual objects may co-exist and interactin real time. Systems and methods disclosed herein address variouschallenges related to VR, AR and MR technology.

A wearable system (also referred to herein as an augmented reality (AR)system) can be configured to present 2D or 3D virtual images to a user.The images may be still images, frames of a video, or a video, incombination or the like. At least a portion of the wearable system canbe implemented on a wearable device that can present a VR, AR, or MRenvironment, alone or in combination, for user interaction. The wearabledevice can be used interchangeably as an AR device (ARD). Further, forthe purpose of the present disclosure, the term “AR” is usedinterchangeably with the term “MR”.

FIG. 1 depicts an illustration of a mixed reality scenario with certainvirtual reality objects, and certain physical objects viewed by aperson. In FIG. 1, an MR scene 100 is depicted wherein a user of an MRtechnology sees a real-world park-like setting 110 featuring people,trees, buildings in the background, and a concrete platform 120. Inaddition to these items, the user of the MR technology also perceivesthat he “sees” a robot statue 130 standing upon the real-world platform120, and a cartoon-like avatar character 140 flying by which seems to bea personification of a bumble bee, even though these elements do notexist in the real world.

In order for the 3D display to produce a true sensation of depth, andmore specifically, a simulated sensation of surface depth, it may bedesirable for each point in the display's visual field to generate anaccommodative response corresponding to its virtual depth. If theaccommodative response to a display point does not correspond to thevirtual depth of that point, as determined by the binocular depth cuesof convergence and stereopsis, the human eye may experience anaccommodation conflict, resulting in unstable imaging, harmful eyestrain, headaches, and, in the absence of accommodation information,almost a complete lack of surface depth.

VR, AR, and MR experiences can be provided by display systems havingdisplays in which images corresponding to a plurality of depth planesare provided to a viewer. The images may be different for each depthplane (e.g., provide slightly different presentations of a scene orobject) and may be separately focused by the viewer's eyes, therebyhelping to provide the user with depth cues based on the accommodationof the eye required to bring into focus different image features for thescene located on different depth plane or based on observing differentimage features on different depth planes being out of focus. Asdiscussed elsewhere herein, such depth cues provide credible perceptionsof depth.

FIG. 2 illustrates an example of wearable system 200 which can beconfigured to provide an AR/VR/MR scene. The wearable system 200 canalso be referred to as the AR system 200. The wearable system 200includes a display 220, and various mechanical and electronic modulesand systems to support the functioning of display 220. The display 220may be coupled to a frame 230, which is wearable by a user, wearer, orviewer 210. The display 220 can be positioned in front of the eyes ofthe user 210. The display 220 can present AR/VR/MR content to a user.The display 220 can comprise a head mounted display (HMD) that is wornon the head of the user.

In some embodiments, a speaker 240 is coupled to the frame 230 andpositioned adjacent the ear canal of the user (in some embodiments,another speaker, not shown, is positioned adjacent the other ear canalof the user to provide for stereo/shapeable sound control). The display220 can include an audio sensor (e.g., a microphone) 232 for detectingan audio stream from the environment and capture ambient sound. In someembodiments, one or more other audio sensors, not shown, are positionedto provide stereo sound reception. Stereo sound reception can be used todetermine the location of a sound source. The wearable system 200 canperform voice or speech recognition on the audio stream.

The wearable system 200 can include an outward-facing imaging system 464(shown in FIG. 4) which observes the world in the environment around theuser. The wearable system 200 can also include an inward-facing imagingsystem 462 (shown in FIG. 4) which can track the eye movements of theuser. The inward-facing imaging system may track either one eye'smovements or both eyes' movements. The inward-facing imaging system 462may be attached to the frame 230 and may be in electrical communicationwith the processing modules 260 or 270, which may process imageinformation acquired by the inward-facing imaging system to determine,e.g., the pupil diameters or orientations of the eyes, eye movements oreye pose of the user 210. The inward-facing imaging system 462 mayinclude one or more cameras. For example, at least one camera may beused to image each eye. The images acquired by the cameras may be usedto determine pupil size or eye pose for each eye separately, therebyallowing presentation of image information to each eye to be dynamicallytailored to that eye.

As an example, the wearable system 200 can use the outward-facingimaging system 464 or the inward-facing imaging system 462 to acquireimages of a pose of the user. The images may be still images, frames ofa video, or a video.

The display 220 can be operatively coupled 250, such as by a wired leador wireless connectivity, to a local data processing module 260 whichmay be mounted in a variety of configurations, such as fixedly attachedto the frame 230, fixedly attached to a helmet or hat worn by the user,embedded in headphones, or otherwise removably attached to the user 210(e.g., in a backpack-style configuration, in a belt-coupling styleconfiguration).

The local processing and data module 260 may comprise a hardwareprocessor, as well as digital memory, such as non-volatile memory (e.g.,flash memory), both of which may be utilized to assist in theprocessing, caching, and storage of data. The data may include data a)captured from sensors (which may be, e.g., operatively coupled to theframe 230 or otherwise attached to the user 210), such as image capturedevices (e.g., cameras in the inward-facing imaging system or theoutward-facing imaging system), audio sensors (e.g., microphones),inertial measurement units (IMUs), accelerometers, compasses, globalpositioning system (GPS) units, radio devices, or gyroscopes; or b)acquired or processed using remote processing module 270 or remote datarepository 280, possibly for passage to the display 220 after suchprocessing or retrieval. The local processing and data module 260 may beoperatively coupled by communication links 262 or 264, such as via wiredor wireless communication links, to the remote processing module 270 orremote data repository 280 such that these remote modules are availableas resources to the local processing and data module 260. In addition,remote processing module 280 and remote data repository 280 may beoperatively coupled to each other.

In some embodiments, the remote processing module 270 may comprise oneor more processors configured to analyze and process data or imageinformation. In some embodiments, the remote data repository 280 maycomprise a digital data storage facility, which may be available throughthe internet or other networking configuration in a “cloud” resourceconfiguration. In some embodiments, all data is stored and allcomputations are performed in the local processing and data module,allowing fully autonomous use from a remote module.

In various embodiments, the local processing and data module 260 or theremote processing module 270 (and remote data repository 280) canperform the techniques for avatar facial expression representation inmultidimensional space that are described herein (see, e.g., FIGS.11-18).

Example Components of A Wearable System

FIG. 3 schematically illustrates example components of a wearablesystem. FIG. 3 shows a wearable system 200 which can include a display220 and a frame 230. A blown-up view 202 schematically illustratesvarious components of the wearable system 200. In certain implements,one or more of the components illustrated in FIG. 3 can be part of thedisplay 220. The various components alone or in combination can collecta variety of data (such as e.g., audio or visual data) associated withthe user of the wearable system 200 or the user's environment. It shouldbe appreciated that other embodiments may have additional or fewercomponents depending on the application for which the wearable system isused. Nevertheless, FIG. 3 provides a basic idea of some of the variouscomponents and types of data that may be collected, analyzed, and storedthrough the wearable system.

FIG. 3 shows an example wearable system 200 which can include thedisplay 220. The display 220 can comprise a display lens 226 that may bemounted to a user's head or a housing or frame 230, which corresponds tothe frame 230. The display lens 226 may comprise one or more transparentmirrors positioned by the housing 230 in front of the user's eyes 302,304 and may be configured to bounce projected light 338 into the eyes302, 304 and facilitate beam shaping, while also allowing fortransmission of at least some light from the local environment. Thewavefront of the projected light beam 338 may be bent or focused tocoincide with a desired focal distance of the projected light. Asillustrated, two wide-field-of-view machine vision cameras 316 (alsoreferred to as world cameras) can be coupled to the housing 230 to imagethe environment around the user. These cameras 316 can be dual capturevisible light/non-visible (e.g., infrared) light cameras. The cameras316 may be part of the outward-facing imaging system 464 shown in FIG.4. Image acquired by the world cameras 316 can be processed by the poseprocessor 336. For example, the pose processor 336 can implement one ormore object recognizers 708 (e.g., shown in FIG. 7) to identify a poseof a user or another person in the user's environment or to identify aphysical object in the user's environment.

With continued reference to FIG. 3, a pair of scanned-lasershaped-wavefront (e.g., for depth) light projector modules with displaymirrors and optics configured to project light 338 into the eyes 302,304 are shown. The depicted view also shows two miniature infraredcameras 324 paired with infrared light (such as light emitting diodes“LED”s), which are configured to be able to track the eyes 302, 304 ofthe user to support rendering and user input. The cameras 324 may bepart of the inward-facing imaging system 462 shown in FIG. 4 Thewearable system 200 can further feature a sensor assembly 339, which maycomprise X, Y, and Z axis accelerometer capability as well as a magneticcompass and X, Y, and Z axis gyro capability, preferably providing dataat a relatively high frequency, such as 200 Hz. The sensor assembly 339may be part of the IMU described with reference to FIG. 2A The depictedsystem 200 can also comprise a head pose processor 336, such as an ASIC(application specific integrated circuit), FPGA (field programmable gatearray), or ARM processor (advanced reduced-instruction-set machine),which may be configured to calculate real or near-real time user headpose from wide field of view image information output from the capturedevices 316. The head pose processor 336 can be a hardware processor andcan be implemented as part of the local processing and data module 260shown in FIG. 2A.

The wearable system can also include one or more depth sensors 234. Thedepth sensor 234 can be configured to measure the distance between anobject in an environment to a wearable device. The depth sensor 234 mayinclude a laser scanner (e.g., a lidar), an ultrasonic depth sensor, ora depth sensing camera. In certain implementations, where the cameras316 have depth sensing ability, the cameras 316 may also be consideredas depth sensors 234.

Also shown is a processor 332 configured to execute digital or analogprocessing to derive pose from the gyro, compass, or accelerometer datafrom the sensor assembly 339. The processor 332 may be part of the localprocessing and data module 260 shown in FIG. 2. The wearable system 200as shown in FIG. 3 can also include a position system such as, e.g., aGPS 337 (global positioning system) to assist with pose and positioninganalyses. In addition, the GPS may further provide remotely-based (e.g.,cloud-based) information about the user's environment. This informationmay be used for recognizing objects or information in user'senvironment.

The wearable system may combine data acquired by the GPS 337 and aremote computing system (such as, e.g., the remote processing module270, another user's ARD, etc.) which can provide more information aboutthe user's environment. As one example, the wearable system candetermine the user's location based on GPS data and retrieve a world map(e.g., by communicating with a remote processing module 270) includingvirtual objects associated with the user's location. As another example,the wearable system 200 can monitor the environment using the worldcameras 316 (which may be part of the outward-facing imaging system 464shown in FIG. 4). Based on the images acquired by the world cameras 316,the wearable system 200 can detect objects in the environment (e.g., byusing one or more object recognizers 708 shown in FIG. 7). The wearablesystem can further use data acquired by the GPS 337 to interpret thecharacters.

The wearable system 200 may also comprise a rendering engine 334 whichcan be configured to provide rendering information that is local to theuser to facilitate operation of the scanners and imaging into the eyesof the user, for the user's view of the world. The rendering engine 334may be implemented by a hardware processor (such as, e.g., a centralprocessing unit or a graphics processing unit). In some embodiments, therendering engine is part of the local processing and data module 260.The rendering engine 334 can be communicatively coupled (e.g., via wiredor wireless links) to other components of the wearable system 200. Forexample, the rendering engine 334, can be coupled to the eye cameras 324via communication link 274, and be coupled to a projecting subsystem 318(which can project light into user's eyes 302, 304 via a scanned laserarrangement in a manner similar to a retinal scanning display) via thecommunication link 272. The rendering engine 334 can also be incommunication with other processing units such as, e.g., the sensor poseprocessor 332 and the image pose processor 336 via links 276 and 294respectively.

The cameras 324 (e.g., mini infrared cameras) may be utilized to trackthe eye pose to support rendering and user input. Some example eye posesmay include where the user is looking or at what depth he or she isfocusing (which may be estimated with eye vergence). The GPS 337, gyros,compass, and accelerometers 339 may be utilized to provide coarse orfast pose estimates. One or more of the cameras 316 can acquire imagesand pose, which in conjunction with data from an associated cloudcomputing resource, may be utilized to map the local environment andshare user views with others.

The example components depicted in FIG. 3 are for illustration purposesonly. Multiple sensors and other functional modules are shown togetherfor ease of illustration and description. Some embodiments may includeonly one or a subset of these sensors or modules. Further, the locationsof these components are not limited to the positions depicted in FIG. 3.Some components may be mounted to or housed within other components,such as a belt-mounted component, a hand-held component, or a helmetcomponent. As one example, the image pose processor 336, sensor poseprocessor 332, and rendering engine 334 may be positioned in a beltpackand configured to communicate with other components of the wearablesystem via wireless communication, such as ultra-wideband, Wi-Fi,Bluetooth, etc., or via wired communication. The depicted housing 230preferably is head-mountable and wearable by the user. However, somecomponents of the wearable system 200 may be worn to other portions ofthe user's body. For example, the speaker 240 may be inserted into theears of a user to provide sound to the user.

Regarding the projection of light 338 into the eyes 302, 304 of theuser, in some embodiment, the cameras 324 may be utilized to measurewhere the centers of a user's eyes are geometrically verged to, which,in general, coincides with a position of focus, or “depth of focus”, ofthe eyes. A 3-dimensional surface of all points the eyes verge to can bereferred to as the “horopter”. The focal distance may take on a finitenumber of depths, or may be infinitely varying. Light projected from thevergence distance appears to be focused to the subject eye 302, 304,while light in front of or behind the vergence distance is blurred.Examples of wearable devices and other display systems of the presentdisclosure are also described in U.S. Patent Publication No.2016/0270656, which is incorporated by reference herein in its entirety.

The human visual system is complicated and providing a realisticperception of depth is challenging. Viewers of an object may perceivethe object as being three-dimensional due to a combination of vergenceand accommodation. Vergence movements (e.g., rolling movements of thepupils toward or away from each other to converge the lines of sight ofthe eyes to fixate upon an object) of the two eyes relative to eachother are closely associated with focusing (or “accommodation”) of thelenses of the eyes. Under normal conditions, changing the focus of thelenses of the eyes, or accommodating the eyes, to change focus from oneobject to another object at a different distance will automaticallycause a matching change in vergence to the same distance, under arelationship known as the “accommodation-vergence reflex.” Likewise, achange in vergence will trigger a matching change in accommodation,under normal conditions. Display systems that provide a better matchbetween accommodation and vergence may form more realistic andcomfortable simulations of three-dimensional imagery.

Further spatially coherent light with a beam diameter of less than about0.7 millimeters can be correctly resolved by the human eye regardless ofwhere the eye focuses. Thus, to create an illusion of proper focaldepth, the eye vergence may be tracked with the cameras 324, and therendering engine 334 and projection subsystem 318 may be utilized torender all objects on or close to the horopter in focus, and all otherobjects at varying degrees of defocus (e.g., using intentionally-createdblurring). Preferably, the system 220 renders to the user at a framerate of about 60 frames per second or greater. As described above,preferably, the cameras 324 may be utilized for eye tracking, andsoftware may be configured to pick up not only vergence geometry butalso focus location cues to serve as user inputs. Preferably, such adisplay system is configured with brightness and contrast suitable forday or night use.

In some embodiments, the display system preferably has latency of lessthan about 20 milliseconds for visual object alignment, less than about0.1 degree of angular alignment, and about 1 arc minute of resolution,which, without being limited by theory, is believed to be approximatelythe limit of the human eye. The display system 220 may be integratedwith a localization system, which may involve GPS elements, opticaltracking, compass, accelerometers, or other data sources, to assist withposition and pose determination; localization information may beutilized to facilitate accurate rendering in the user's view of thepertinent world (e.g., such information would facilitate the glasses toknow where they are with respect to the real world).

In some embodiments, the wearable system 200 is configured to displayone or more virtual images based on the accommodation of the user'seyes. Unlike prior 3D display approaches that force the user to focuswhere the images are being projected, in some embodiments, the wearablesystem is configured to automatically vary the focus of projectedvirtual content to allow for a more comfortable viewing of one or moreimages presented to the user. For example, if the user's eyes have acurrent focus of 1 m, the image may be projected to coincide with theuser's focus. If the user shifts focus to 3 m, the image is projected tocoincide with the new focus. Thus, rather than forcing the user to apredetermined focus, the wearable system 200 of some embodiments allowsthe user's eye to a function in a more natural manner.

Such a wearable system 200 may eliminate or reduce the incidences of eyestrain, headaches, and other physiological symptoms typically observedwith respect to virtual reality devices. To achieve this, variousembodiments of the wearable system 200 are configured to project virtualimages at varying focal distances, through one or more variable focuselements (VFEs). In one or more embodiments, 3D perception may beachieved through a multi-plane focus system that projects images atfixed focal planes away from the user. Other embodiments employ variableplane focus, wherein the focal plane is moved back and forth in thez-direction to coincide with the user's present state of focus.

In both the multi-plane focus systems and variable plane focus systems,wearable system 200 may employ eye tracking to determine a vergence ofthe user's eyes, determine the user's current focus, and project thevirtual image at the determined focus. In other embodiments, wearablesystem 200 comprises a light modulator that variably projects, through afiber scanner, or other light generating source, light beams of varyingfocus in a raster pattern across the retina. Thus, the ability of thedisplay of the wearable system 200 to project images at varying focaldistances not only eases accommodation for the user to view objects in3D, but may also be used to compensate for user ocular anomalies, asfurther described in U.S. Patent Publication No. 2016/0270656, which isincorporated by reference herein in its entirety. In some otherembodiments, a spatial light modulator may project the images to theuser through various optical components. For example, as describedfurther below, the spatial light modulator may project the images ontoone or more waveguides, which then transmit the images to the user.

Waveguide Stack Assembly

FIG. 4 illustrates an example of a waveguide stack for outputting imageinformation to a user. A wearable system 400 includes a stack ofwaveguides, or stacked waveguide assembly 480 that may be utilized toprovide three-dimensional perception to the eye/brain using a pluralityof waveguides 432 b, 434 b, 436 b, 438 b, 4400 b. In some embodiments,the wearable system 400 may correspond to wearable system 200 of FIG. 2,with FIG. 4 schematically showing some parts of that wearable system 200in greater detail. For example, in some embodiments, the waveguideassembly 480 may be integrated into the display 220 of FIG. 2.

With continued reference to FIG. 4, the waveguide assembly 480 may alsoinclude a plurality of features 458, 456, 454, 452 between thewaveguides. In some embodiments, the features 458, 456, 454, 452 may belenses. In other embodiments, the features 458, 456, 454, 452 may not belenses. Rather, they may simply be spacers (e.g., cladding layers orstructures for forming air gaps).

The waveguides 432 b, 434 b, 436 b, 438 b, 440 b or the plurality oflenses 458, 456, 454, 452 may be configured to send image information tothe eye with various levels of wavefront curvature or light raydivergence. Each waveguide level may be associated with a particulardepth plane and may be configured to output image informationcorresponding to that depth plane. Image injection devices 420, 422,424, 426, 428 may be utilized to inject image information into thewaveguides 440 b, 438 b, 436 b, 434 b, 432 b, each of which may beconfigured to distribute incoming light across each respectivewaveguide, for output toward the eye 410. Light exits an output surfaceof the image injection devices 420, 422, 424, 426, 428 and is injectedinto a corresponding input edge of the waveguides 440 b, 438 b, 436 b,434 b, 432 b. In some embodiments, a single beam of light (e.g., acollimated beam) may be injected into each waveguide to output an entirefield of cloned collimated beams that are directed toward the eye 410 atparticular angles (and amounts of divergence) corresponding to the depthplane associated with a particular waveguide.

In some embodiments, the image injection devices 420, 422, 424, 426, 428are discrete displays that each produce image information for injectioninto a corresponding waveguide 440 b, 438 b, 436 b, 434 b, 432 b,respectively. In some other embodiments, the image injection devices420, 422, 424, 426, 428 are the output ends of a single multiplexeddisplay which may, e.g., pipe image information via one or more opticalconduits (such as fiber optic cables) to each of the image injectiondevices 420, 422, 424, 426, 428.

A controller 460 controls the operation of the stacked waveguideassembly 480 and the image injection devices 420, 422, 424, 426, 428.The controller 460 includes programming (e.g., instructions in anon-transitory computer-readable medium) that regulates the timing andprovision of image information to the waveguides 440 b, 438 b, 436 b,434 b, 432 b. In some embodiments, the controller 460 may be a singleintegral device, or a distributed system connected by wired or wirelesscommunication channels. The controller 460 may be part of the processingmodules 260 or 270 (illustrated in FIG. 2) in some embodiments.

The waveguides 440 b, 438 b, 436 b, 434 b, 432 b may be configured topropagate light within each respective waveguide by total internalreflection (TIR). The waveguides 440 b, 438 b, 436 b, 434 b, 432 b mayeach be planar or have another shape (e.g., curved), with major top andbottom surfaces and edges extending between those major top and bottomsurfaces. In the illustrated configuration, the waveguides 440 b, 438 b,436 b, 434 b, 432 b may each include light extracting optical elements440 a, 438 a, 436 a, 434 a, 432 a that are configured to extract lightout of a waveguide by redirecting the light, propagating within eachrespective waveguide, out of the waveguide to output image informationto the eye 410. Extracted light may also be referred to as outcoupledlight, and light extracting optical elements may also be referred to asoutcoupling optical elements. An extracted beam of light is outputted bythe waveguide at locations at which the light propagating in thewaveguide strikes a light redirecting element. The light extractingoptical elements (440 a, 438 a, 436 a, 434 a, 432 a) may, for example,be reflective or diffractive optical features. While illustrateddisposed at the bottom major surfaces of the waveguides 440 b, 438 b,436 b, 434 b, 432 b for ease of description and drawing clarity, in someembodiments, the light extracting optical elements 440 a, 438 a, 436 a,434 a, 432 a may be disposed at the top or bottom major surfaces, or maybe disposed directly in the volume of the waveguides 440 b, 438 b, 436b, 434 b, 432 b. In some embodiments, the light extracting opticalelements 440 a, 438 a, 436 a, 434 a, 432 a may be formed in a layer ofmaterial that is attached to a transparent substrate to form thewaveguides 440 b, 438 b, 436 b, 434 b, 432 b. In some other embodiments,the waveguides 440 b, 438 b, 436 b, 434 b, 432 b may be a monolithicpiece of material and the light extracting optical elements 440 a, 438a, 436 a, 434 a, 432 a may be formed on a surface or in the interior ofthat piece of material.

With continued reference to FIG. 4, as discussed herein, each waveguide440 b, 438 b, 436 b, 434 b, 432 b is configured to output light to forman image corresponding to a particular depth plane. For example, thewaveguide 432 b nearest the eye may be configured to deliver collimatedlight, as injected into such waveguide 432 b, to the eye 410. Thecollimated light may be representative of the optical infinity focalplane. The next waveguide up 434 b may be configured to send outcollimated light which passes through the first lens 452 (e.g., anegative lens) before it can reach the eye 410. First lens 452 may beconfigured to create a slight convex wavefront curvature so that theeye/brain interprets light coming from that next waveguide up 434 b ascoming from a first focal plane closer inward toward the eye 410 fromoptical infinity. Similarly, the third up waveguide 436 b passes itsoutput light through both the first lens 452 and second lens 454 beforereaching the eye 410. The combined optical power of the first and secondlenses 452 and 454 may be configured to create another incrementalamount of wavefront curvature so that the eye/brain interprets lightcoming from the third waveguide 436 b as coming from a second focalplane that is even closer inward toward the person from optical infinitythan was light from the next waveguide up 434 b.

The other waveguide layers (e.g., waveguides 438 b, 440 b) and lenses(e.g., lenses 456, 458) are similarly configured, with the highestwaveguide 440 b in the stack sending its output through all of thelenses between it and the eye for an aggregate focal powerrepresentative of the closest focal plane to the person. To compensatefor the stack of lenses 458, 456, 454, 452 when viewing/interpretinglight coming from the world 470 on the other side of the stackedwaveguide assembly 480, a compensating lens layer 430 may be disposed atthe top of the stack to compensate for the aggregate power of the lensstack 458, 456, 454, 452 below. Such a configuration provides as manyperceived focal planes as there are available waveguide/lens pairings.Both the light extracting optical elements of the waveguides and thefocusing aspects of the lenses may be static (e.g., not dynamic orelectro-active). In some alternative embodiments, either or both may bedynamic using electro-active features.

With continued reference to FIG. 4, the light extracting opticalelements 440 a, 438 a, 436 a, 434 a, 432 a may be configured to bothredirect light out of their respective waveguides and to output thislight with the appropriate amount of divergence or collimation for aparticular depth plane associated with the waveguide. As a result,waveguides having different associated depth planes may have differentconfigurations of light extracting optical elements, which output lightwith a different amount of divergence depending on the associated depthplane. In some embodiments, as discussed herein, the light extractingoptical elements 440 a, 438 a, 436 a, 434 a, 432 a may be volumetric orsurface features, which may be configured to output light at specificangles. For example, the light extracting optical elements 440 a, 438 a,436 a, 434 a, 432 a may be volume holograms, surface holograms, and/ordiffraction gratings. Light extracting optical elements, such asdiffraction gratings, are described in U.S. Patent Publication No.2015/0178939, published Jun. 25, 2015, which is incorporated byreference herein in its entirety.

In some embodiments, the light extracting optical elements 440 a, 438 a,436 a, 434 a, 432 a are diffractive features that form a diffractionpattern, or “diffractive optical element” (also referred to herein as a“DOE”). Preferably, the DOE has a relatively low diffraction efficiencyso that only a portion of the light of the beam is deflected away towardthe eye 410 with each intersection of the DOE, while the rest continuesto move through a waveguide via total internal reflection. The lightcarrying the image information can thus be divided into a number ofrelated exit beams that exit the waveguide at a multiplicity oflocations and the result is a fairly uniform pattern of exit emissiontoward the eye 304 for this particular collimated beam bouncing aroundwithin a waveguide.

In some embodiments, one or more DOEs may be switchable between “on”state in which they actively diffract, and “off” state in which they donot significantly diffract. For instance, a switchable DOE may comprisea layer of polymer dispersed liquid crystal, in which microdropletscomprise a diffraction pattern in a host medium, and the refractiveindex of the microdroplets can be switched to substantially match therefractive index of the host material (in which case the pattern doesnot appreciably diffract incident light) or the microdroplet can beswitched to an index that does not match that of the host medium (inwhich case the pattern actively diffracts incident light).

In some embodiments, the number and distribution of depth planes ordepth of field may be varied dynamically based on the pupil sizes ororientations of the eyes of the viewer. Depth of field may changeinversely with a viewer's pupil size. As a result, as the sizes of thepupils of the viewer's eyes decrease, the depth of field increases suchthat one plane that is not discernible because the location of thatplane is beyond the depth of focus of the eye may become discernible andappear more in focus with reduction of pupil size and commensurate withthe increase in depth of field. Likewise, the number of spaced apartdepth planes used to present different images to the viewer may bedecreased with the decreased pupil size. For example, a viewer may notbe able to clearly perceive the details of both a first depth plane anda second depth plane at one pupil size without adjusting theaccommodation of the eye away from one depth plane and to the otherdepth plane. These two depth planes may, however, be sufficiently infocus at the same time to the user at another pupil size withoutchanging accommodation.

In some embodiments, the display system may vary the number ofwaveguides receiving image information based upon determinations ofpupil size or orientation, or upon receiving electrical signalsindicative of particular pupil size or orientation. For example, if theuser's eyes are unable to distinguish between two depth planesassociated with two waveguides, then the controller 460 (which may be anembodiment of the local processing and data module 260) can beconfigured or programmed to cease providing image information to one ofthese waveguides. Advantageously, this may reduce the processing burdenon the system, thereby increasing the responsiveness of the system. Inembodiments in which the DOEs for a waveguide are switchable between theon and off states, the DOEs may be switched to the off state when thewaveguide does receive image information.

In some embodiments, it may be desirable to have an exit beam meet thecondition of having a diameter that is less than the diameter of the eyeof a viewer. However, meeting this condition may be challenging in viewof the variability in size of the viewer's pupils. In some embodiments,this condition is met over a wide range of pupil sizes by varying thesize of the exit beam in response to determinations of the size of theviewer's pupil. For example, as the pupil size decreases, the size ofthe exit beam may also decrease. In some embodiments, the exit beam sizemay be varied using a variable aperture.

The wearable system 400 can include an outward-facing imaging system 464(e.g., a digital camera) that images a portion of the world 470. Thisportion of the world 470 may be referred to as the field of view (FOV)of a world camera and the imaging system 464 is sometimes referred to asan FOV camera. The FOV of the world camera may or may not be the same asthe FOV of a viewer 210 which encompasses a portion of the world 470 theviewer 210 perceives at a given time. For example, in some situations,the FOV of the world camera may be larger than the viewer 210 of theviewer 210 of the wearable system 400. The entire region available forviewing or imaging by a viewer may be referred to as the field of regard(FOR). The FOR may include 4π steradians of solid angle surrounding thewearable system 400 because the wearer can move his body, head, or eyesto perceive substantially any direction in space. In other contexts, thewearer's movements may be more constricted, and accordingly the wearer'sFOR may subtend a smaller solid angle. Images obtained from theoutward-facing imaging system 464 can be used to track gestures made bythe user (e.g., hand or finger gestures), detect objects in the world470 in front of the user, and so forth.

The wearable system 400 can include an audio sensor 232, e.g., amicrophone, to capture ambient sound. As described above, in someembodiments, one or more other audio sensors can be positioned toprovide stereo sound reception useful to the determination of locationof a speech source. The audio sensor 232 can comprise a directionalmicrophone, as another example, which can also provide such usefuldirectional information as to where the audio source is located. Thewearable system 400 can use information from both the outward-facingimaging system 464 and the audio sensor 230 in locating a source ofspeech, or to determine an active speaker at a particular moment intime, etc. For example, the wearable system 400 can use the voicerecognition alone or in combination with a reflected image of thespeaker (e.g., as seen in a mirror) to determine the identity of thespeaker. As another example, the wearable system 400 can determine aposition of the speaker in an environment based on sound acquired fromdirectional microphones. The wearable system 400 can parse the soundcoming from the speaker's position with speech recognition algorithms todetermine the content of the speech and use voice recognition techniquesto determine the identity (e.g., name or other demographic information)of the speaker.

The wearable system 400 can also include an inward-facing imaging system466 (e.g., a digital camera), which observes the movements of the user,such as the eye movements and the facial movements. The inward-facingimaging system 466 may be used to capture images of the eye 410 todetermine the size and/or orientation of the pupil of the eye 304. Theinward-facing imaging system 466 can be used to obtain images for use indetermining the direction the user is looking (e.g., eye pose) or forbiometric identification of the user (e.g., via iris identification). Insome embodiments, at least one camera may be utilized for each eye, toseparately determine the pupil size or eye pose of each eyeindependently, thereby allowing the presentation of image information toeach eye to be dynamically tailored to that eye. In some otherembodiments, the pupil diameter or orientation of only a single eye 410(e.g., using only a single camera per pair of eyes) is determined andassumed to be similar for both eyes of the user. The images obtained bythe inward-facing imaging system 466 may be analyzed to determine theuser's eye pose or mood, which can be used by the wearable system 400 todecide which audio or visual content should be presented to the user.The wearable system 400 may also determine head pose (e.g., headposition or head orientation) using sensors such as IMUs,accelerometers, gyroscopes, etc.

The wearable system 400 can include a user input device 466 by which theuser can input commands to the controller 460 to interact with thewearable system 400. For example, the user input device 466 can includea trackpad, a touchscreen, a joystick, a multiple degree-of-freedom(DOF) controller, a capacitive sensing device, a game controller, akeyboard, a mouse, a directional pad (D-pad), a wand, a haptic device, atotem (e.g., functioning as a virtual user input device), and so forth.A multi-DOF controller can sense user input in some or all possibletranslations (e.g., left/right, forward/backward, or up/down) orrotations (e.g., yaw, pitch, or roll) of the controller. A multi-DOFcontroller which supports the translation movements may be referred toas a 3DOF while a multi-DOF controller which supports the translationsand rotations may be referred to as 6DOF. In some cases, the user mayuse a finger (e.g., a thumb) to press or swipe on a touch-sensitiveinput device to provide input to the wearable system 400 (e.g., toprovide user input to a user interface provided by the wearable system400). The user input device 466 may be held by the user's hand duringthe use of the wearable system 400. The user input device 466 can be inwired or wireless communication with the wearable system 400.

Other Components of the Wearable System

In many implementations, the wearable system may include othercomponents in addition or in alternative to the components of thewearable system described above. The wearable system may, for example,include one or more haptic devices or components. The haptic devices orcomponents may be operable to provide a tactile sensation to a user. Forexample, the haptic devices or components may provide a tactilesensation of pressure or texture when touching virtual content (e.g.,virtual objects, virtual tools, other virtual constructs). The tactilesensation may replicate a feel of a physical object which a virtualobject represents, or may replicate a feel of an imagined object orcharacter (e.g., a dragon) which the virtual content represents. In someimplementations, haptic devices or components may be worn by the user(e.g., a user wearable glove). In some implementations, haptic devicesor components may be held by the user.

The wearable system may, for example, include one or more physicalobjects which are manipulable by the user to allow input or interactionwith the wearable system. These physical objects may be referred toherein as totems. Some totems may take the form of inanimate objects,such as for example, a piece of metal or plastic, a wall, a surface oftable. In certain implementations, the totems may not actually have anyphysical input structures (e.g., keys, triggers, joystick, trackball,rocker switch). Instead, the totem may simply provide a physicalsurface, and the wearable system may render a user interface so as toappear to a user to be on one or more surfaces of the totem. Forexample, the wearable system may render an image of a computer keyboardand trackpad to appear to reside on one or more surfaces of a totem. Forexample, the wearable system may render a virtual computer keyboard andvirtual trackpad to appear on a surface of a thin rectangular plate ofaluminum which serves as a totem. The rectangular plate does not itselfhave any physical keys or trackpad or sensors. However, the wearablesystem may detect user manipulation or interaction or touches with therectangular plate as selections or inputs made via the virtual keyboardor virtual trackpad. The user input device 466 (shown in FIG. 4) may bean embodiment of a totem, which may include a trackpad, a touchpad, atrigger, a joystick, a trackball, a rocker or virtual switch, a mouse, akeyboard, a multi-degree-of-freedom controller, or another physicalinput device. A user may use the totem, alone or in combination withposes, to interact with the wearable system or other users.

Examples of haptic devices and totems usable with the wearable devices,HMD, and display systems of the present disclosure are described in U.S.Patent Publication No. 2015/0016777, which is incorporated by referenceherein in its entirety.

Example Processes of User Interactions with A Wearable System

FIG. 5 is a process flow diagram of an example of a method 500 forinteracting with a virtual user interface. The method 500 may beperformed by the wearable system described herein. Embodiments of themethod 500 can be used by the wearable system to detect persons ordocuments in the FOV of the wearable system.

At block 510, the wearable system may identify a particular UI. The typeof UI may be predetermined by the user. The wearable system may identifythat a particular UI needs to be populated based on a user input (e.g.,gesture, visual data, audio data, sensory data, direct command, etc.).The UI can be specific to a security scenario where the wearer of thesystem is observing users who present documents to the wearer (e.g., ata travel checkpoint). At block 520, the wearable system may generatedata for the virtual UI. For example, data associated with the confines,general structure, shape of the UI etc., may be generated. In addition,the wearable system may determine map coordinates of the user's physicallocation so that the wearable system can display the UI in relation tothe user's physical location. For example, if the UI is body centric,the wearable system may determine the coordinates of the user's physicalstance, head pose, or eye pose such that a ring UI can be displayedaround the user or a planar UI can be displayed on a wall or in front ofthe user. In the security context described herein, the UI may bedisplayed as if the UI were surrounding the traveler who is presentingdocuments to the wearer of the system, so that the wearer can readilyview the UI while looking at the traveler and the traveler's documents.If the UI is hand centric, the map coordinates of the user's hands maybe determined. These map points may be derived through data receivedthrough the FOV cameras, sensory input, or any other type of collecteddata.

At block 530, the wearable system may send the data to the display fromthe cloud or the data may be sent from a local database to the displaycomponents. At block 540, the UI is displayed to the user based on thesent data. For example, a light field display can project the virtual UIinto one or both of the user's eyes. Once the virtual UI has beencreated, the wearable system may simply wait for a command from the userto generate more virtual content on the virtual UI at block 550. Forexample, the UI may be a body centric ring around the user's body or thebody of a person in the user's environment (e.g., a traveler). Thewearable system may then wait for the command (a gesture, a head or eyemovement, voice command, input from a user input device, etc.), and ifit is recognized (block 560), virtual content associated with thecommand may be displayed to the user (block 570).

Examples of Avatar Rendering in Mixed Reality

A wearable system may employ various mapping related techniques in orderto achieve high depth of field in the rendered light fields. In mappingout the virtual world, it is advantageous to know all the features andpoints in the real world to accurately portray virtual objects inrelation to the real world. To this end, FOV images captured from usersof the wearable system can be added to a world model by including newpictures that convey information about various points and features ofthe real world. For example, the wearable system can collect a set ofmap points (such as 2D points or 3D points) and find new map points torender a more accurate version of the world model. The world model of afirst user can be communicated (e.g., over a network such as a cloudnetwork) to a second user so that the second user can experience theworld surrounding the first user.

FIG. 6A is a block diagram of another example of a wearable system whichcan comprise an avatar processing and rendering system 690 in a mixedreality environment. The wearable system 600 may be part of the wearablesystem 200 shown in FIG. 2. In this example, the wearable system 600 cancomprise a map 620, which may include at least a portion of the data inthe map database 710 (shown in FIG. 7). The map may partly residelocally on the wearable system, and may partly reside at networkedstorage locations accessible by wired or wireless network (e.g., in acloud system). A pose process 610 may be executed on the wearablecomputing architecture (e.g., processing module 260 or controller 460)and utilize data from the map 620 to determine position and orientationof the wearable computing hardware or user. Pose data may be computedfrom data collected on the fly as the user is experiencing the systemand operating in the world. The data may comprise images, data fromsensors (such as inertial measurement units, which generally compriseaccelerometer and gyroscope components) and surface informationpertinent to objects in the real or virtual environment.

A sparse point representation may be the output of a simultaneouslocalization and mapping (e.g., SLAM or vSLAM, referring to aconfiguration wherein the input is images/visual only) process. Thesystem can be configured to not only find out where in the world thevarious components are, but what the world is made of. Pose may be abuilding block that achieves many goals, including populating the mapand using the data from the map.

In one embodiment, a sparse point position may not be completelyadequate on its own, and further information may be needed to produce amultifocal AR, VR, or MR experience. Dense representations, generallyreferring to depth map information, may be utilized to fill this gap atleast in part. Such information may be computed from a process referredto as Stereo 640, wherein depth information is determined using atechnique such as triangulation or time-of-flight sensing. Imageinformation and active patterns (such as infrared patterns created usingactive projectors), images acquired from image cameras, or handgestures/totem 650 may serve as input to the Stereo process 640. Asignificant amount of depth map information may be fused together, andsome of this may be summarized with a surface representation. Forexample, mathematically definable surfaces may be efficient (e.g.,relative to a large point cloud) and digestible inputs to otherprocessing devices like game engines. Thus, the output of the stereoprocess (e.g., a depth map) 640 may be combined in the fusion process630. Pose 610 may be an input to this fusion process 630 as well, andthe output of fusion 630 becomes an input to populating the map process620. Sub-surfaces may connect with each other, such as in topographicalmapping, to form larger surfaces, and the map becomes a large hybrid ofpoints and surfaces.

To resolve various aspects in a mixed reality process 660, variousinputs may be utilized. For example, in the embodiment depicted in FIG.6A, Game parameters may be inputs to determine that the user of thesystem is playing a monster battling game with one or more monsters atvarious locations, monsters dying or running away under variousconditions (such as if the user shoots the monster), walls or otherobjects at various locations, and the like. The world map may includeinformation regarding the location of the objects or semanticinformation of the objects (e.g., classifications such as whether theobject is flat or round, horizontal or vertical, a table or a lamp,etc.) and the world map can be another valuable input to mixed reality.Pose relative to the world becomes an input as well and plays a key roleto almost any interactive system.

Controls or inputs from the user are another input to the wearablesystem 600. As described herein, user inputs can include visual input,gestures, totems, audio input, sensory input, etc. In order to movearound or play a game, for example, the user may need to instruct thewearable system 600 regarding what he or she wants to do. Beyond justmoving oneself in space, there are various forms of user controls thatmay be utilized. In one embodiment, a totem (e.g. a user input device),or an object such as a toy gun may be held by the user and tracked bythe system. The system preferably will be configured to know that theuser is holding the item and understand what kind of interaction theuser is having with the item (e.g., if the totem or object is a gun, thesystem may be configured to understand location and orientation, as wellas whether the user is clicking a trigger or other sensed button orelement which may be equipped with a sensor, such as an IMU, which mayassist in determining what is going on, even when such activity is notwithin the field of view of any of the cameras.)

Hand gesture tracking or recognition may also provide input information.The wearable system 600 may be configured to track and interpret handgestures for button presses, for gesturing left or right, stop, grab,hold, etc. For example, in one configuration, the user may want to flipthrough emails or a calendar in a non-gaming environment, or do a “fistbump” with another person or player. The wearable system 600 may beconfigured to leverage a minimum amount of hand gesture, which may ormay not be dynamic. For example, the gestures may be simple staticgestures like open hand for stop, thumbs up for ok, thumbs down for notok; or a hand flip right, or left, or up/down for directional commands.

Eye tracking is another input (e.g., tracking where the user is lookingto control the display technology to render at a specific depth orrange). In one embodiment, vergence of the eyes may be determined usingtriangulation, and then using a vergence/accommodation model developedfor that particular person, accommodation may be determined. Eyetracking can be performed by the eye camera(s) to determine eye gaze(e.g., direction or orientation of one or both eyes). Other techniquescan be used for eye tracking such as, e.g., measurement of electricalpotentials by electrodes placed near the eye(s) (e.g.,electrooculography).

Speech tracking can be another input can be used alone or in combinationwith other inputs (e.g., totem tracking, eye tracking, gesture tracking,etc.). Speech tracking may include speech recognition, voicerecognition, alone or in combination. The system 600 can include anaudio sensor (e.g., a microphone) that receives an audio stream from theenvironment. The system 600 can incorporate voice recognition technologyto determine who is speaking (e.g., whether the speech is from thewearer of the ARD or another person or voice (e.g., a recorded voicetransmitted by a loudspeaker in the environment)) as well as speechrecognition technology to determine what is being said. The local data &processing module 260 or the remote processing module 270 can processthe audio data from the microphone (or audio data in another stream suchas, e.g., a video stream being watched by the user) to identify contentof the speech by applying various speech recognition algorithms, suchas, e.g., hidden Markov models, dynamic time warping (DTW)-based speechrecognitions, neural networks, deep learning algorithms such as deepfeedforward and recurrent neural networks, end-to-end automatic speechrecognitions, machine learning algorithms (described with reference toFIG. 7), or other algorithms that uses acoustic modeling or languagemodeling, etc.

The local data & processing module 260 or the remote processing module270 can also apply voice recognition algorithms which can identify theidentity of the speaker, such as whether the speaker is the user 210 ofthe wearable system 600 or another person with whom the user isconversing. Some example voice recognition algorithms can includefrequency estimation, hidden Markov models, Gaussian mixture models,pattern matching algorithms, neural networks, matrix representation,Vector Quantization, speaker diarisation, decision trees, and dynamictime warping (DTW) technique. Voice recognition techniques can alsoinclude anti-speaker techniques, such as cohort models, and worldmodels. Spectral features may be used in representing speakercharacteristics. The local data & processing module or the remote dataprocessing module 270 can use various machine learning algorithmsdescribed with reference to FIG. 7 to perform the voice recognition.

An implementation of a wearable system can use these user controls orinputs via a UI. UI elements (e.g., controls, popup windows, bubbles,data entry fields, etc.) can be used, for example, to dismiss a displayof information, e.g., graphics or semantic information of an object.

With regard to the camera systems, the example wearable system 600 shownin FIG. 6A can include three pairs of cameras: a relative wide FOV orpassive SLAM pair of cameras arranged to the sides of the user's face, adifferent pair of cameras oriented in front of the user to handle thestereo imaging process 640 and also to capture hand gestures andtotem/object tracking in front of the user's face. The FOV cameras andthe pair of cameras for the stereo process 640 may be a part of theoutward-facing imaging system 464 (shown in FIG. 4). The wearable system600 can include eye tracking cameras (which may be a part of aninward-facing imaging system 462 shown in FIG. 4) oriented toward theeyes of the user in order to triangulate eye vectors and otherinformation. The wearable system 600 may also comprise one or moretextured light projectors (such as infrared (IR) projectors) to injecttexture into a scene.

The wearable system 600 can comprise an avatar processing and renderingsystem 690. The avatar processing and rendering system 690 can beconfigured to generate, update, animate, and render an avatar based oncontextual information. Some or all of the avatar processing andrendering system 690 can be implemented as part of the local processingand data module 260 or the remote processing module 262, 264 alone or incombination. In various embodiments, multiple avatar processing andrendering systems 690 (e.g., as implemented on different wearabledevices) can be used for rendering the virtual avatar 670. For example,a first user's wearable device may be used to determine the first user'sintent, while a second user's wearable device can determine an avatar'scharacteristics and render the avatar of the first user based on theintent received from the first user's wearable device. The first user'swearable device and the second user's wearable device (or other suchwearable devices) can communicate via a network, for example, as will bedescribed with reference to FIGS. 9A and 9B.

FIG. 6B illustrates an example avatar processing and rendering system690. The example avatar processing and rendering system 690 can comprisea 3D model processing system 680, a contextual information analysissystem 688, an avatar autoscaler 692, an intent mapping system 694, ananatomy adjustment system 698, a stimuli response system 696, alone orin combination. The system 690 is intended to illustrate functionalitiesfor avatar processing and rendering and is not intended to be limiting.For example, in certain implementations, one or more of these systemsmay be part of another system. For example, portions of the contextualinformation analysis system 688 may be part of the avatar autoscaler692, intent mapping system 694, stimuli response system 696, or anatomyadjustment system 698, individually or in combination.

The contextual information analysis system 688 can be configured todetermine environment and object information based on one or more devicesensors described with reference to FIGS. 2 and 3. For example, thecontextual information analysis system 688 can analyze environments andobjects (including physical or virtual objects) of a user's environmentor an environment in which the user's avatar is rendered, using imagesacquired by the outward-facing imaging system 464 of the user or theviewer of the user's avatar. The contextual information analysis system688 can analyze such images alone or in combination with a data acquiredfrom location data or world maps (e.g., maps 620, 710, 910) to determinethe location and layout of objects in the environments. The contextualinformation analysis system 688 can also access biological features ofthe user or human in general for animating the virtual avatar 670realistically. For example, the contextual information analysis system688 can generate a discomfort curve which can be applied to the avatarsuch that a portion of the user's avatar's body (e.g., the head) is notat an uncomfortable (or unrealistic) position with respect to the otherportions of the user's body (e.g., the avatar's head is not turned 270degrees). In certain implementations, one or more object recognizers 708(shown in FIG. 7) may be implemented as part of the contextualinformation analysis system 688.

The avatar autoscaler 692, the intent mapping system 694, and thestimuli response system 696, and anatomy adjustment system 698 can beconfigured to determine the avatar's characteristics based on contextualinformation. Some example characteristics of the avatar can include thesize, appearance, position, orientation, movement, pose, expression,etc. The avatar autoscaler 692 can be configured to automatically scalethe avatar such that the user does not have to look at the avatar at anuncomfortable pose. For example, the avatar autoscaler 692 can increaseor decrease the size of the avatar to bring the avatar to the user's eyelevel such that the user does not need to look down at the avatar orlook up at the avatar respectively. The intent mapping system 694 candetermine an intent of a user's interaction and map the intent to anavatar (rather than the exact user interaction) based on the environmentthat the avatar is rendered in. For example, an intent of a first usermay be to communicate with a second user in a telepresence session (see,e.g., FIG. 9B). Typically, two people face each other whencommunicating. The intent mapping system 694 of the first user'swearable system can determine that such a face-to-face intent existsduring the telepresence session and can cause the first user's wearablesystem to render the second user's avatar to be facing the first user.If the second user were to physically turn around, instead of renderingthe second user's avatar in a turned position (which would cause theback of the second user's avatar to be rendered to the first user), thefirst user's intent mapping system 694 can continue to render the secondavatar's face to the first user, which is the inferred intent of thetelepresence session (e.g., face-to-face intent in this example).

The stimuli response system 696 can identify an object of interest inthe environment and determine an avatar's response to the object ofinterest. For example, the stimuli response system 696 can identify asound source in an avatar's environment and automatically turn theavatar to look at the sound source. The stimuli response system 696 canalso determine a threshold termination condition. For example, thestimuli response system 696 can cause the avatar to go back to itsoriginal pose after the sound source disappears or after a period oftime has elapsed.

The anatomy adjustment system 698 can be configured to adjust the user'spose based on biological features. For example, the anatomy adjustmentsystem 698 can be configured to adjust relative positions between theuser's head and the user's torso or between the user's upper body andlower body based on a discomfort curve.

The 3D model processing system 680 can be configured to animate andcause the display 220 to render a virtual avatar 670. The 3D modelprocessing system 680 can include a virtual character processing system682 and a movement processing system 684. The virtual characterprocessing system 682 can be configured to generate and update a 3Dmodel of a user (for creating and animating the virtual avatar). Themovement processing system 684 can be configured to animate the avatar,such as, e.g., by changing the avatar's pose, by moving the avatararound in a user's environment, or by animating the avatar's facialexpressions, etc. As will further be described herein, the virtualavatar can be animated using rigging techniques. In some embodiments, anavatar is represented in two parts: a surface representation (e.g., adeformable mesh) that is used to render the outward appearance of thevirtual avatar and a hierarchical set of interconnected joints (e.g., acore skeleton) for animating the mesh. In some implementations, thevirtual character processing system 682 can be configured to edit orgenerate surface representations, while the movement processing system684 can be used to animate the avatar by moving the avatar, deformingthe mesh, etc. At least one of the virtual character processing system682 or the movement processing system 684 can be configured to implementthe techniques described with reference to FIGS. 11-18 to providerealistic facial expressions and transitions between the facialexpressions.

Examples of Mapping a User's Environment

FIG. 7 is a block diagram of an example of an MR environment 700. The MRenvironment 700 may be configured to receive input (e.g., visual input702 from the user's wearable system, stationary input 704 such as roomcameras, sensory input 706 from various sensors, gestures, totems, eyetracking, user input from the user input device 466 etc.) from one ormore user wearable systems (e.g., wearable system 200 or display system220) or stationary room systems (e.g., room cameras, etc.). The wearablesystems can use various sensors (e.g., accelerometers, gyroscopes,temperature sensors, movement sensors, depth sensors, GPS sensors,inward-facing imaging system, outward-facing imaging system, etc.) todetermine the location and various other attributes of the environmentof the user. This information may further be supplemented withinformation from stationary cameras in the room that may provide imagesor various cues from a different point of view. The image data acquiredby the cameras (such as the room cameras and/or the cameras of theoutward-facing imaging system) may be reduced to a set of mappingpoints.

One or more object recognizers 708 can crawl through the received data(e.g., the collection of points) and recognize or map points, tagimages, attach semantic information to objects with the help of a mapdatabase 710. The map database 710 may comprise various points collectedover time and their corresponding objects. The various devices and themap database can be connected to each other through a network (e.g.,LAN, WAN, etc.) to access the cloud.

Based on this information and collection of points in the map database,the object recognizers 708 a to 708 n may recognize objects in anenvironment. For example, the object recognizers can recognize faces,persons, windows, walls, user input devices, televisions, documents(e.g., travel tickets, driver's license, passport as described in thesecurity examples herein), other objects in the user's environment, etc.One or more object recognizers may be specialized for object withcertain characteristics. For example, the object recognizer 708 a may beused to recognizer faces, while another object recognizer may be usedrecognize documents.

The object recognitions may be performed using a variety of computervision techniques. For example, the wearable system can analyze theimages acquired by the outward-facing imaging system 464 (shown in FIG.4) to perform scene reconstruction, event detection, video tracking,object recognition (e.g., persons or documents), object pose estimation,facial recognition (e.g., from a person in the environment or an imageon a document), learning, indexing, motion estimation, or image analysis(e.g., identifying indicia within documents such as photos, signatures,identification information, travel information, etc.), and so forth. Oneor more computer vision algorithms may be used to perform these tasks.Non-limiting examples of computer vision algorithms include:Scale-invariant feature transform (SIFT), speeded up robust features(SURF), oriented FAST and rotated BRIEF (ORB), binary robust invariantscalable keypoints (BRISK), fast retina keypoint (FREAK), Viola-Jonesalgorithm, Eigenfaces approach, Lucas-Kanade algorithm, Horn-Schunkalgorithm, Mean-shift algorithm, visual simultaneous location andmapping (vSLAM) techniques, a sequential Bayesian estimator (e.g.,Kalman filter, extended Kalman filter, etc.), bundle adjustment,Adaptive thresholding (and other thresholding techniques), IterativeClosest Point (ICP), Semi Global Matching (SGM), Semi Global BlockMatching (SGBM), Feature Point Histograms, various machine learningalgorithms (such as e.g., support vector machine, k-nearest neighborsalgorithm, Naive Bayes, neural network (including convolutional or deepneural networks), or other supervised/unsupervised models, etc.), and soforth.

The object recognitions can additionally or alternatively be performedby a variety of machine learning algorithms. Once trained, the machinelearning algorithm can be stored by the HMD. Some examples of machinelearning algorithms can include supervised or non-supervised machinelearning algorithms, including regression algorithms (such as, forexample, Ordinary Least Squares Regression), instance-based algorithms(such as, for example, Learning Vector Quantization), decision treealgorithms (such as, for example, classification and regression trees),Bayesian algorithms (such as, for example, Naive Bayes), clusteringalgorithms (such as, for example, k-means clustering), association rulelearning algorithms (such as, for example, a-priori algorithms),artificial neural network algorithms (such as, for example, Perceptron),deep learning algorithms (such as, for example, Deep Boltzmann Machine,or deep neural network), dimensionality reduction algorithms (such as,for example, Principal Component Analysis), ensemble algorithms (suchas, for example, Stacked Generalization), and/or other machine learningalgorithms. In some embodiments, individual models can be customized forindividual data sets. For example, the wearable device can generate orstore a base model. The base model may be used as a starting point togenerate additional models specific to a data type (e.g., a particularuser in the telepresence session), a data set (e.g., a set of additionalimages obtained of the user in the telepresence session), conditionalsituations, or other variations. In some embodiments, the wearable HMDcan be configured to utilize a plurality of techniques to generatemodels for analysis of the aggregated data. Other techniques may includeusing pre-defined thresholds or data values.

Based on this information and collection of points in the map database,the object recognizers 708 a to 708 n may recognize objects andsupplement objects with semantic information to give life to theobjects. For example, if the object recognizer recognizes a set ofpoints to be a door, the system may attach some semantic information(e.g., the door has a hinge and has a 90 degree movement about thehinge). If the object recognizer recognizes a set of points to be amirror, the system may attach semantic information that the mirror has areflective surface that can reflect images of objects in the room. Thesemantic information can include affordances of the objects as describedherein. For example, the semantic information may include a normal ofthe object. The system can assign a vector whose direction indicates thenormal of the object. Over time the map database grows as the system(which may reside locally or may be accessible through a wirelessnetwork) accumulates more data from the world. Once the objects arerecognized, the information may be transmitted to one or more wearablesystems. For example, the MR environment 700 may include informationabout a scene happening in California. The environment 700 may betransmitted to one or more users in New York. Based on data receivedfrom an FOV camera and other inputs, the object recognizers and othersoftware components can map the points collected from the variousimages, recognize objects etc., such that the scene may be accurately“passed over” to a second user, who may be in a different part of theworld. The environment 700 may also use a topological map forlocalization purposes.

FIG. 8 is a process flow diagram of an example of a method 800 ofrendering virtual content in relation to recognized objects. The method800 describes how a virtual scene may be presented to a user of thewearable system. The user may be geographically remote from the scene.For example, the user may be in New York, but may want to view a scenethat is presently going on in California, or may want to go on a walkwith a friend who resides in California.

At block 810, the wearable system may receive input from the user andother users regarding the environment of the user. This may be achievedthrough various input devices, and knowledge already possessed in themap database. The user's FOV camera, sensors, GPS, eye tracking, etc.,convey information to the system at block 810. The system may determinesparse points based on this information at block 820. The sparse pointsmay be used in determining pose data (e.g., head pose, eye pose, bodypose, or hand gestures) that can be used in displaying and understandingthe orientation and position of various objects in the user'ssurroundings. The object recognizers 708 a-708 n may crawl through thesecollected points and recognize one or more objects using a map databaseat block 830. This information may then be conveyed to the user'sindividual wearable system at block 840, and the desired virtual scenemay be accordingly displayed to the user at block 850. For example, thedesired virtual scene (e.g., user in CA) may be displayed at theappropriate orientation, position, etc., in relation to the variousobjects and other surroundings of the user in New York.

Example Communications among Multiple Wearable Systems

FIG. 9A schematically illustrates an overall system view depictingmultiple user devices interacting with each other. The computingenvironment 900 includes user devices 930 a, 930 b, 930 c. The userdevices 930 a, 930 b, and 930 c can communicate with each other througha network 990. The user devices 930 a-930 c can each include a networkinterface to communicate via the network 990 with a remote computingsystem 920 (which may also include a network interface 971). The network990 may be a LAN, WAN, peer-to-peer network, radio, Bluetooth, or anyother network. The computing environment 900 can also include one ormore remote computing systems 920. The remote computing system 920 mayinclude server computer systems that are clustered and located atdifferent geographic locations. The user devices 930 a, 930 b, and 930 cmay communicate with the remote computing system 920 via the network990.

The remote computing system 920 may include a remote data repository 980which can maintain information about a specific user's physical and/orvirtual worlds. Data storage 980 can store information related to users,users' environment (e.g., world maps of the user's environment), orconfigurations of avatars of the users. The remote data repository maybe an embodiment of the remote data repository 280 shown in FIG. 2. Theremote computing system 920 may also include a remote processing module970. The remote processing module 970 may be an embodiment of the remoteprocessing module 270 shown in FIG. 2. The remote processing module 970may include one or more processors which can communicate with the userdevices (930 a, 930 b, 930 c) and the remote data repository 980. Theprocessors can process information obtained from user devices and othersources. In some implementations, at least a portion of the processingor storage can be provided by the local processing and data module 260(as shown in FIG. 2). The remote computing system 920 may enable a givenuser to share information about the specific user's own physical and/orvirtual worlds with another user.

The user device may be a wearable device (such as an HMD or an ARD), acomputer, a mobile device, or any other devices alone or in combination.For example, the user devices 930 b and 930 c may be an embodiment ofthe wearable system 200 shown in FIG. 2 (or the wearable system 400shown in FIG. 4) which can be configured to present AR/VR/MR content.

One or more of the user devices can be used with the user input device466 shown in FIG. 4. A user device can obtain information about the userand the user's environment (e.g., using the outward-facing imagingsystem 464 shown in FIG. 4). The user device and/or remote computingsystem 1220 can construct, update, and build a collection of images,points and other information using the information obtained from theuser devices. For example, the user device may process raw informationacquired and send the processed information to the remote computingsystem 1220 for further processing. The user device may also send theraw information to the remote computing system 1220 for processing. Theuser device may receive the processed information from the remotecomputing system 1220 and provide final processing before projecting tothe user. The user device may also process the information obtained andpass the processed information to other user devices. The user devicemay communicate with the remote data repository 1280 while processingacquired information. Multiple user devices and/or multiple servercomputer systems may participate in the construction and/or processingof acquired images.

The information on the physical worlds may be developed over time andmay be based on the information collected by different user devices.Models of virtual worlds may also be developed over time and be based onthe inputs of different users. Such information and models can sometimesbe referred to herein as a world map or a world model. As described withreference to FIGS. 6 and 7, information acquired by the user devices maybe used to construct a world map 910. The world map 910 may include atleast a portion of the map 620 described in FIG. 6A. Various objectrecognizers (e.g. 708 a, 708 b, 708 c . . . 708 n) may be used torecognize objects and tag images, as well as to attach semanticinformation to the objects. These object recognizers are also describedin FIG. 7.

The remote data repository 980 can be used to store data and tofacilitate the construction of the world map 910. The user device canconstantly update information about the user's environment and receiveinformation about the world map 910. The world map 910 may be created bythe user or by someone else. As discussed herein, user devices (e.g. 930a, 930 b, 930 c) and remote computing system 920, alone or incombination, may construct and/or update the world map 910. For example,a user device may be in communication with the remote processing module970 and the remote data repository 980. The user device may acquireand/or process information about the user and the user's environment.The remote processing module 970 may be in communication with the remotedata repository 980 and user devices (e.g. 930 a, 930 b, 930 c) toprocess information about the user and the user's environment. Theremote computing system 920 can modify the information acquired by theuser devices (e.g. 930 a, 930 b, 930 c), such as, e.g. selectivelycropping a user's image, modifying the user's background, adding virtualobjects to the user's environment, annotating a user's speech withauxiliary information, etc. The remote computing system 920 can send theprocessed information to the same and/or different user devices.

Examples of a Telepresence Session

FIG. 9B depicts an example where two users of respective wearablesystems are conducting a telepresence session. Two users (named Alice912 and Bob 914 in this example) are shown in this figure. The two usersare wearing their respective wearable devices 902 and 904 which caninclude an HMD described with reference to FIG. 2 (e.g., the displaydevice 220 of the system 200) for representing a virtual avatar of theother user in the telepresence session. The two users can conduct atelepresence session using the wearable device. Note that the verticalline in FIG. 9B separating the two users is intended to illustrate thatAlice 912 and Bob 914 may (but need not) be in two different locationswhile they communicate via telepresence (e.g., Alice may be inside heroffice in Atlanta while Bob is outdoors in Boston).

As described with reference to FIG. 9A, the wearable devices 902 and 904may be in communication with each other or with other user devices andcomputer systems. For example, Alice's wearable device 902 may be incommunication with Bob's wearable device 904, e.g., via the network 990(shown in FIG. 9A). The wearable devices 902 and 904 can track theusers' environments and movements in the environments (e.g., via therespective outward-facing imaging system 464, or one or more locationsensors) and speech (e.g., via the respective audio sensor 232). Thewearable devices 902 and 904 can also track the users' eye movements orgaze based on data acquired by the inward-facing imaging system 462. Insome situations, the wearable device can also capture or track a user'sfacial expressions or other body movements (e.g., arm or leg movements)where a user is near a reflective surface and the outward-facing imagingsystem 464 can obtain reflected images of the user to observe the user'sfacial expressions or other body movements.

A wearable device can use information acquired of a first user and theenvironment to animate a virtual avatar that will be rendered by asecond user's wearable device to create a tangible sense of presence ofthe first user in the second user's environment. For example, thewearable devices 902 and 904, the remote computing system 920, alone orin combination, may process Alice's images or movements for presentationby Bob's wearable device 904 or may process Bob's images or movementsfor presentation by Alice's wearable device 902. As further describedherein, the avatars can be rendered based on contextual information suchas, e.g., a user's intent, an environment of the user or an environmentin which the avatar is rendered, or other biological features of ahuman.

Although the examples only refer to two users, the techniques describedherein should not be limited to two users. Multiple users (e.g., two,three, four, five, six, or more) using wearables (or other telepresencedevices) may participate in a telepresence session. A particular user'swearable device can present to that particular user the avatars of theother users during the telepresence session. Further, while the examplesin this figure show users as standing in an environment, the users arenot required to stand. Any of the users may stand, sit, kneel, lie down,walk or run, or be in any position or movement during a telepresencesession. The user may also be in a physical environment other thandescribed in examples herein. The users may be in separate environmentsor may be in the same environment while conducting the telepresencesession. Not all users are required to wear their respective HMDs in thetelepresence session. For example, Alice 912 may use other imageacquisition and display devices such as a webcam and computer screenwhile Bob 914 wears the wearable device 904.

Examples of a Virtual Avatar

FIG. 10 illustrates an example of an avatar as perceived by a user of awearable system. The example avatar 1000 shown in FIG. 10 can be anavatar of Alice 912 (shown in FIG. 9B) standing behind a physical plantin a room. An avatar can include various characteristics, such as forexample, size, appearance (e.g., skin color, complexion, hair style,clothes, facial features, such as wrinkles, moles, blemishes, pimples,dimples, etc.), position, orientation, movement, pose, expression, etc.These characteristics may be based on the user associated with theavatar (e.g., the avatar 1000 of Alice may have some or allcharacteristics of the actual person Alice 912). As further describedherein, the avatar 1000 can be animated based on contextual information,which can include adjustments to one or more of the characteristics ofthe avatar 1000. Although generally described herein as representing thephysical appearance of the person (e.g., Alice), this is forillustration and not limitation. Alice's avatar could represent theappearance of another real or fictional human being besides Alice, apersonified object, a creature, or any other real or fictitiousrepresentation. Further, the plant in FIG. 10 need not be physical, butcould be a virtual representation of a plant that is presented to theuser by the wearable system. Also, additional or different virtualcontent than shown in FIG. 10 could be presented to the user.

Examples of Rigging Systems for Virtual Characters

An animated virtual character, such as a human avatar, can be wholly orpartially represented in computer graphics as a polygon mesh. A polygonmesh, or simply “mesh” for short, is a collection of points in a modeledthree-dimensional space. The mesh can form a polyhedral object whosesurfaces define the body or shape of the virtual character (or a portionthereof). While meshes can include any number of points (withinpractical limits which may be imposed by available computing power),finer meshes with more points are generally able to portray morerealistic virtual characters with finer details that may closelyapproximate real life people, animals, objects, etc. FIG. 10 shows anexample of a mesh 1010 around an eye of the avatar 1000.

Each point in the mesh can be defined by a coordinate in the modeledthree-dimensional space. The modeled three-dimensional space can be, forexample, a Cartesian space addressed by (x, y, z) coordinates. Thepoints in the mesh are the vertices of the polygons which make up thepolyhedral object. Each polygon represents a surface, or face, of thepolyhedral object and is defined by an ordered set of vertices, with thesides of each polygon being straight line edges connecting the orderedset of vertices. In some cases, the polygon vertices in a mesh maydiffer from geometric polygons in that they are not necessarily coplanarin 3D graphics. In addition, the vertices of a polygon in a mesh may bycollinear, in which case the polygon has zero area (referred to as adegenerate polygon).

In some embodiments, a mesh is made up of three-vertex polygons (i.e.,triangles or “tris” for short) or four-vertex polygons (i.e.,quadrilaterals or “quads” for short). However, higher-order polygons canalso be used in some meshes. Meshes are typically quad-based in directcontent creation (DCC) applications (e.g., applications such as Maya(available from Autodesk, Inc.) or Houdini (available from Side EffectsSoftware Inc.) which are primarily designed for creating andmanipulating 3D computer graphics), whereas meshes are typicallytri-based in real-time applications.

To animate a virtual character, its mesh can be deformed by moving someor all of its vertices to new positions in space at various instants intime. The deformations can represent both large-scale movements (e.g.,movement of limbs) and fine movements (e.g., facial movements). Theseand other deformations can be based on real-world models (e.g.,photogrammetric scans of real humans performing body movements,articulations, facial contortions, expressions, etc.), art-directeddevelopment (which may be based on real-world sampling), combinations ofthe same, or other techniques. In the early days of computer graphics,mesh deformations could be accomplished manually by independentlysetting new positions for the vertices, but given the size andcomplexity of modern meshes it is typically desirable to producedeformations using automated systems and processes. The control systems,processes, and techniques for producing these deformations are referredto as rigging, or simply “the rig.” The example avatar processing andrendering system 690 of FIG. 6B includes a 3D model processing system680 which can implement rigging and which can be programmed to performthe techniques for avatar facial expression representation inmultidimensional space that are described herein (see, e.g., FIGS.11-19).

The rigging for a virtual character can use skeletal systems to assistwith mesh deformations. A skeletal system includes a collection ofjoints which correspond to points of articulation for the mesh. In thecontext of rigging, joints are sometimes also referred to as “bones”despite the difference between these terms when used in the anatomicalsense. Joints in a skeletal system can move, or otherwise change, withrespect to one another according to transforms which can be applied tothe joints. The transforms can include translations or rotations inspace, as well as other operations. The joints can be assignedhierarchical relationships (e.g., parent-child relationships) withrespect to one another. These hierarchical relationships can allow onejoint to inherit transforms or other characteristics from another joint.For example, a child joint in a skeletal system can inherit a transformassigned to its parent joint so as to cause the child joint to movetogether with the parent joint.

A skeletal system for a virtual character can be defined with joints atappropriate positions, and with appropriate local axes of rotation,degrees of freedom, etc., to allow for a desired set of meshdeformations to be carried out. Once a skeletal system has been definedfor a virtual character, each joint can be assigned, in a process called“skinning,” an amount of influence over the various vertices in themesh. This can be done by assigning a weight value to each vertex foreach joint in the skeletal system. When a transform is applied to anygiven joint, the vertices under its influence can be moved, or otherwisealtered, automatically based on that joint transform by amounts whichcan be dependent upon their respective weight values.

A rig can include multiple skeletal systems. One type of skeletal systemis a core skeleton (also referred to as a low-order skeleton) which canbe used to control large-scale movements of the virtual character. Inthe case of a human avatar, for example, the core skeleton mightresemble the anatomical skeleton of a human. Although the core skeletonfor rigging purposes may not map exactly to an anatomically-correctskeleton, it may have a sub-set of joints in analogous locations withanalogous orientations and movement properties.

As briefly mentioned above, a skeletal system of joints can behierarchical with, for example, parent-child relationships among joints.When a transform (e.g., a change in position and/or orientation) isapplied to a particular joint in the skeletal system, the same transformcan be applied to all other lower-level joints within the samehierarchy. In the case of a rig for a human avatar, for example, thecore skeleton may include separate joints for the avatar's shoulder,elbow, and wrist. Among these, the shoulder joint may be assigned to thehighest level in the hierarchy, while the elbow joint can be assigned asa child of the shoulder joint, and the wrist joint can be assigned as achild of the elbow joint. Accordingly, when a particular translationand/or rotation transform is applied to the shoulder joint, the sametransform can also be applied to the elbow joint and the wrist jointsuch that they are translated and/or rotated in the same way as theshoulder.

Despite the connotations of its name, a skeletal system in a rig neednot necessarily represent an anatomical skeleton. In rigging, skeletalsystems can represent a wide variety of hierarchies used to controldeformations of the mesh. For example, hair can be represented as aseries of joints in a hierarchical chain; skin motions due to anavatar's facial contortions (which may represent expressions such assmiling, frowning, laughing, speaking, blinking, etc.) can berepresented by a series of facial joints controlled by a facial rig;muscle deformation can be modeled by joints; and motion of clothing canbe represented by a grid of joints.

The rig for a virtual character can include multiple skeletal systems,some of which may drive the movement of others. A lower-order skeletalsystem is one which drives one or more higher-order skeletal systems.Conversely, higher-order skeletal systems are ones which are driven orcontrolled by a lower-order skeletal system. For example, whereas themovements of the core skeleton of a character might be controlledmanually by an animator, the core skeleton can in turn drive or controlthe movements of a higher-order skeletal system. For example,higher-order helper joints—which may not have anatomical analogs in aphysical skeleton—can be provided to improve the mesh deformations whichresult from movements of the core skeleton. The transforms applied tothese and other joints in higher-order skeletal systems may be derivedalgorithmically from the transforms applied to the lower-order skeleton.Higher-order skeletons can represent, for example, muscles, skin, fat,clothing, hair, or any other skeletal system which does not requiredirect animation control.

As already discussed, transforms can be applied to joints in skeletalsystems in order to carry out mesh deformations. In the context ofrigging, transforms include functions which accept one or more givenpoints in 3D space and produce an output of one or more new 3D points.For example, a transform can accept one or more 3D points which define ajoint and can output one or more new 3D points which specify thetransformed joint. Joint transforms can include, for example, atranslation component, a rotation component, and a scale component.

A translation is a transform which moves a set of one or more specifiedpoints in the modeled 3D space by a specified amount with no change inthe orientation or size of the set of points. A rotation is a transformwhich rotates a set of one or more specified points in the modeled 3Dspace about a specified axis by a specified amount (e.g., rotate everypoint in the mesh 45 degrees about the z-axis). An affine transform (or6 degree of freedom (DOF) transform) is one which only includestranslation(s) and rotation(s). Application of an affine transform canbe thought of as moving a set of one or more points in space withoutchanging its size, though the orientation can change.

Meanwhile, a scale transform is one which modifies one or more specifiedpoints in the modeled 3D space by scaling their respective coordinatesby a specified value. This changes the size and/or shape of thetransformed set of points. A uniform scale transform scales eachcoordinate by the same amount, whereas a non-uniform scale transform canscale the (x, y, z) coordinates of the specified points independently. Anon-uniform scale transform can be used, for example, to providesquashing and stretching effects, such as those which may result frommuscular action. Yet another type of transform is a shear transform. Ashear transform is one which modifies a set of one or more specifiedpoints in the modeled 3D space by translating a coordinate of the pointsby different amounts based on the distance of that coordinate from anaxis.

When a transform is applied to a joint to cause it to move, the verticesunder the influence of that joint are also moved. This results indeformations of the mesh. As discussed above, the process of assigningweights to quantify the influence each joint has over each vertex iscalled skinning (or sometimes “weight painting” or “skin weighting”).The weights are typically values between 0 (meaning no influence) and 1(meaning complete influence). Some vertices in the mesh may beinfluenced only by a single joint. In that case those vertices areassigned weight values of 1 for that joint, and their positions arechanged based on transforms assigned to that specific joint but noothers. Other vertices in the mesh may be influenced by multiple joints.In that case, separate weights are assigned to those vertices for all ofthe influencing joints, with the sum of the weights for each vertexequaling 1. The positions of these vertices are changed based ontransforms assigned to all of their influencing joints.

Making weight assignments for all of the vertices in a mesh can beextremely labor intensive, especially as the number of joints increases.Balancing the weights to achieve desired mesh deformations in responseto transforms applied to the joints can be quite difficult for evenhighly trained artists. In the case of real-time applications, the taskcan be complicated further by the fact that many real-time systems alsoenforce limits on the number of joints (generally 8 or fewer) which canbe weighted to a specific vertex. Such limits are typically imposed tofor the sake of efficiency in the graphics processing unit (GPU).

The term skinning can also refer to the process of actually deformingthe mesh, using the assigned weights, based on transforms applied to thejoints in a skeletal system. For example, a series of core skeletonjoint transforms may be specified by an animator to produce a desiredcharacter movement (e.g., a running movement or a dance step). Whentransforms are applied to one or more of the joints, new positions arecalculated for the vertices under the influence of the transformedjoints. The new position for any given vertex is typically computed as aweighted average of all the joint transforms which influence thatparticular vertex. There are many algorithms used for computing thisweighted average, but the most common, and the one used in mostreal-time applications due to its simplicity and ease of control, islinear blend skinning (LBS). In linear blend skinning, a new positionfor each vertex is calculated using each joint transform for which thatvertex has a non-zero weight. Then, the new vertex coordinates resultingfrom each of these joint transforms are averaged in proportion to therespective weights assigned to that vertex for each of the joints. Thereare well known limitations to LBS in practice, and much of the work inmaking high-quality rigs is devoted to finding and overcoming theselimitations. Many helper joint systems are designed specifically forthis purpose.

In addition to skeletal systems, “blendshapes” can also be used inrigging to produce mesh deformations. A blendshape (sometimes alsocalled a “morph target” or just a “shape”) is a deformation applied to aset of vertices in the mesh where each vertex in the set is moved aspecified amount in a specified direction based upon a weight. Eachvertex in the set may have its own custom motion for a specificblendshape, and moving the vertices in the set simultaneously willgenerate the desired shape. The custom motion for each vertex in ablendshape can be specified by a “delta,” which can be a vectorrepresenting the amount and direction of XYZ motion applied to thatvertex. Blendshapes can be used to produce, for example, facialdeformations to move the eyes, lips, brows, nose, dimples, etc., just toname a few possibilities.

Blendshapes are useful for deforming the mesh in an art-directable way.They offer a great deal of control, as the exact shape can be sculptedor captured from a scan of a model. But the benefits of blendshapes comeat the cost of having to store the deltas for all the vertices in theblendshape. For animated characters with fine meshes and manyblendshapes, the amount of delta data can be significant.

Each blendshape can be applied to a specified degree by using blendshapeweights. These weights typically range from 0 (where the blendshape isnot applied at all) to 1 (where the blendshape is fully active). Forexample, a blendshape to move a character's eyes can be applied with asmall weight to move the eyes a small amount, or it can be applied witha large weight to create a larger eye movement.

The rig may apply multiple blendshapes in combinations with one anotherto achieve a desired complex deformation. For example, to produce asmile, the rig may apply blendshapes for lip corner pull, raising theupper lip, and lowering the lower lip, as well as moving the eyes,brows, nose, and dimples. The desired shape from combining two or moreblendshapes is known as a combination shape (or simply a “combo”).

One problem that can result from applying two blendshapes in combinationis that the blendshapes may operate on some of the same vertices. Whenboth blendshapes are active, the result is called a double transform or“going off-model.” The solution to this is typically a correctiveblendshape. A corrective blendshape is a special blendshape whichrepresents a desired deformation with respect to a currently applieddeformation rather than representing a desired deformation with respectto the neutral. Corrective blendshapes (or just “correctives”) can beapplied based upon the weights of the blendshapes they are correcting.For example, the weight for the corrective blendshape can be madeproportionate to the weights of the underlying blendshapes which triggerapplication of the corrective blendshape.

Corrective blendshapes can also be used to correct skinning anomalies orto improve the quality of a deformation. For example, a joint mayrepresent the motion of a specific muscle, but as a single transform itcannot represent all the non-linear behaviors of the skin, fat, andmuscle. Applying a corrective, or a series of correctives, as the muscleactivates can result in more pleasing and convincing deformations.

Rigs are built in layers, with lower, simpler layers often drivinghigher-order layers. This applies to both skeletal systems andblendshape deformations. For example, as already mentioned, the riggingfor an animated virtual character may include higher-order skeletalsystems which are controlled by lower-order skeletal systems. There aremany ways to control a higher-order skeleton or a blendshape based upona lower-order skeleton, including constraints, logic systems, andpose-based deformation.

A constraint can be a system where a particular object or jointtransform controls one or more components of a transform applied toanother joint or object. There are many different types of constraints.For example, aim constraints change the rotation of the target transformto point in specific directions or at specific objects. Parentconstraints act as virtual parent-child relationships between pairs oftransforms. Position constraints constrain a transform to specificpoints or a specific object. Orientation constraints constrain atransform to a specific rotation of an object.

Logic systems are systems of mathematical equations which produce someoutputs given a set of inputs. These are specified, not learned. Forexample, a blendshape value might be defined as the product of two otherblendshapes (this is an example of a corrective shape known as acombination or combo shape).

Pose-based deformations can also be used to control higher-orderskeletal systems or blendshapes. The pose of a skeletal system isdefined by the collection of transforms (e.g., rotation(s) andtranslation(s)) for all the joints in that skeletal system. Poses canalso be defined for subsets of the joints in a skeletal system. Forexample, an arm pose could be defined by the transforms applied to theshoulder, elbow, and wrist joints. A pose space deformer (PSD) is asystem used to determine a deformation output for a particular posebased on one or more “distances” between that pose and a defined pose.These distances can be metrics which characterize how different one ofthe poses is from the other. A PSD can include a pose interpolation nodewhich, for example, accepts a set of joint rotations (defining a pose)as input parameters and in turn outputs normalized per-pose weights todrive a deformer, such as a blendshape. The pose interpolation node canbe implemented in a variety of ways, including with radial basisfunctions (RBF). RBFs can perform a machine-learned mathematicalapproximation of a function. RBFs can be trained using a set of inputsand their associated expected outputs. The training data could be, forexample, multiple sets of joint transforms (which define particularposes) and the corresponding blendshapes to be applied in response tothose poses. Once the function is learned, new inputs (e.g., poses) canbe given and their expected outputs can be computed efficiently. RBFsare a subtype of artificial neural networks. RBFs can be used to drivehigher-level components of a rig based upon the state of lower-levelcomponents. For example, the pose of a core skeleton can drive helperjoints and correctives at higher levels.

These control systems can be chained together to perform complexbehaviors. As an example, an eye rig could contain two “look around”values for horizontal and vertical rotation. These values can be passedthrough some logic to determine the exact rotation of an eye jointtransform, which might in turn be used as an input to an RBF whichcontrols blendshapes that change the shape of the eyelid to match theposition of the eye. The activation values of these shapes might be usedto drive other components of a facial expression using additional logic,and so on.

Some example goals of rigging systems can be to provide a mechanism toproduce pleasing, high-fidelity deformations based on simple,human-understandable control systems. In the case of real-timeapplications, the goal may be to provide rigging systems which aresimple or efficient enough to run in real-time on, for example, aVR/AR/MR system or the computing device 10, while making as fewcompromises to the final quality as possible. In some embodiments, the3D model processing system 680 executes a rigging system to animate anavatar in a mixed reality environment in real-time to be interactive(with users of the VR/AR/MR system) and to provide appropriate,contextual avatar behavior (e.g., intent-based behavior) in the user'senvironment.

Example Controls and Modeling Techniques for Facial Expressions

To provide realistic interactions with a virtual character, variousemotions may be assigned to the virtual character. The virtualcharacter's emotion may change in response to a user's interaction or anevent in the environment (e.g., a loud sound in the physical or virtualenvironment associated with the virtual character). The characterenvironment can also extend beyond those provided by the wearable deviceor beyond the physical environment that the user is currently in. Forexample, the environment can include the Internet or outside physicalenvironment (e.g., where a user at home, the environment may extendbeyond the user's home, such as, e.g., to a park or a stadium). As aresult, the virtual character may also react emotionally to eventshappening outside of its immediate physical or virtual environment. Forexample, the virtual character may react to an incoming message or newsfrom the Internet. The emotions can be expressed through facialexpressions, body language, speech, or movements, or other actions ofthe virtual character.

As described above, the facial expressions of a virtual character can becontrolled by a rigging system. For example, an avatar's facialexpression can be modeled by combinations of blendshapes. Thecombinations of blendshapes can be controlled by values of a facevector. A combination of constituent values of the face vector cancorrespond to a facial expression or an emotion. The face vector cancomprise a number of dimensions (which may also be referred to ascomponents or variables). Each dimension can correspond to a blendshapeor other facial parameter in a rigging model (e.g., an AU of a FACSmodel). The values of a face vector can control one or more vertices ofthe avatar's mesh to achieve the facial expression or the emotion. Thevalues of the variables may be in a floating point number formatalthough other types of data formats (e.g., Boolean or integer) are alsopossible. FIG. 12A shows examples of face vectors for a neutral, asurprised, a shocked, a displeased, and a disgusted expression.

As an example of controlling facial expressions, the face vector forcontrolling facial expressions can comprise 137 variables in someexamples. The value of each variable in the vector can represent aweight of the corresponding blendshape for driving the movement ofvertices of the character's mesh. The weight for one or more of the 137variables can change, depending on the facial expression. As an example,a “happy vector” can include a weight for each of the 137 variables. A“sad vector” has the same 137 variables, except with different weightsthat define a sad expression. Although certain examples herein aredescribed in the context of a 137-dimensional face vector space, this isfor purposes of illustration and not limitation. In other embodiments,the number of components in a face vector can be up to 10, 50, 100, 200,1000, or more.

In certain implementations, the variables can be expressed as facesliders associated with a facial rig. With reference to the aboveexample, where the vector has 137 variables, the facial rig can include137 adjustable controls called sliders. The sliders can be positioned atspecific locations of the face and values for the sliders can beadjusted by the rig to adjust the facial deformation at that location.Adjustments to a face slider can be associated with changes in values ofa variable associated with the slider. The adjustments can include adirection of the movement of the face slider and/or an amount ofmovement of the face slider (e.g., with respect to the previous locationof the face slider). Such adjustments of a slider can control themovement of a set of vertices at certain locations of the mesh. In somesituations, a single vertex can also be controlled by multiple sliders.In some embodiments, a slider can be adjusted through a range of values(e.g., between 0 and 1, between −1 and +1, or between any two numbers).

FIG. 11 illustrates an example of sliders associated with an example ofa facial rig. In this example, the locations of the sliders are assignedbased on action units (AUs) of a facial action coding system (FACS).FACS can decompose a facial expression into isolated muscle contractionsand relaxations. The numerical representation of the isolated musclemovements can be referred to as an AU. Although FACS is used in thisexample rig, other control systems can utilize other methodologies tocharacterize facial musculature or movement.

The facial rig 1100 in FIG. 11 can be used to control facial expressionsof an avatar. The facial rig 1100 can be thought of as an electronicdigital puppet in which points of articulation can be parameterized intoa plurality of sliders (see, e.g., the example sliders 1104, 1108). Thesliders 1104, 1108 can be directly mapped to AUs of the FACScharacterization of the human face. For example, arrows 1104 correspondto an AU parameter and lines 1108 indicate the directionality of theAUs. The sliders 1104, 1108 can be adjusted electronically to controlthe deformation of the avatar's mesh. The controls (e.g., facial rigparameters 1104, 1108) can be driven in real time by the facial rig 1100and can be parameterized to a normalized value, such as between −1 and 1or between 0 and 1. By normalizing the controls, the values can be usedfrom rig to rig. For example, if a FACS session is performed for a humanmodel, the animation system can advantageously re-use that data on anavatar for another person.

The combinations of the AUs can aggregate to form representations ofemotional (or expression) states of the human face (sometimes referredto as AU variants). Further, an intensity scale (e.g., between 0% and100%) may be included for each AU of the AU variant. For example, theexpression “Happy” can correspond to AUs 12 (lip corner puller) (100%),25 (lips apart) (100%), and 6 (Cheek Raiser) (51%). In some cases, ifthe intensity is not specified, the intensity will be set at a defaultvalue (e.g., 100%). For example, in some cases, “Happy” can berepresented as the AU variants [(12, 25, 6 (51%)].

Various other expressions can also be represented, including, but notlimited to, sad, fearful, angry, surprised, or disgusted. For example,the expression “Sad” can correspond to AUs: 4 (Brow Lowerer) (100%), 15(Lip Corner Depressor) (100%), 1 (Inner Brow Raiser) (60%), 6 (CheekRaiser) (50%), 11 (Nasolabial Deepener) (26%), and 17 (Chin Raiser)(67%). Thus, “Sad” can be represented as AU variant [4, 15, 1 (60%), 6(50%), 11 (26%), 17 (67%)]. The expression “Fearful” can correspond toAUs: 1 (Inner Brow Raiser) (100%), 4 (Brow Lowerer) (100%), 20 (Lipstretcher) (100%), 25 (Lips part) (100%), 2 (Outer Brow Raiser) (57%), 5(Upper Lid Raiser) (63%), 26 (Jaw Drop) (33%). Thus, “Fearful” can berepresented as AU variant [1, 4, 20, 25, 2 (57%), 5 (63%), 26 (33%)].The expression “Angry” can correspond to AUs: 4 (Brow Lowerer) (100%), 7(Lid Tightener) (100%), 24 (Lip Pressor) (100%), 10 (Upper Lip Raiser)(26%), 17 (Chin Raiser) (52%), 23 (Lip Tightener) (29%). Thus, “Angry”can be represented as AU variant [4, 7, 24, 10 (26%), 17 (52%), 23(29%)]. The expression “Surprised” can correspond to AUs: 1 (Inner BrowRaiser) (100%), 2 (Outer Brow Raiser) (100%), 25 (Lips part) (100%), 26(Jaw Drop) (100%), 5 (Upper Lid Raiser) (66%). Thus, “Surprised” can berepresented as AU variant [1, 2, 25, 26, 5 (66%)]. The expression“Disgusted” can correspond to AUs: 9 (Nose Wrinkler) (100%), 10 (UpperLip Raiser) (100%), 17 (Chin Raiser) (100%), 4 (Brow Lowerer) (31%), 24(Lip Pressor) (26%). Thus, “Disgusted” can be represented as AU variant[9, 10, 17, 4 (31%), 24 (26%)]. Accordingly, by knowing the AUs and/orAU variants used for a particular animation, the system (e.g., thecomputing device 10) can identify one or more emotions associated withthat set of AUs and/or AU variants.

Although many of the AU variants may be based on FACS, some expressionsmay be different from traditional FACS groupings. For example, varioussystems may utilize different AUs or different intensity scales torepresent an emotion or expression. Accordingly, the sliders 1104, 1108can be coarsely mapped in real time. For example, if a real personsmiles, the wearable system may interpret this as happy, and the avatarcan be manipulated as a “happy” category (rather than point-to-pointmatching of the real person). This may simplify the computational loadof the system. Additional examples related to rigs for manipulatingfacial expressions using sliders are also described in U.S. ProvisionalApplication No. 62/643,548, entitled “ANIMATING VIRTUAL AVATAR FACIALMOVEMENTS”, filed Mar. 15, 2018, the disclosure of which is herebyincorporated by reference herein in its entirety.

FIG. 12A illustrates examples of face vectors representative of facialexpressions. This figure shows an example table 1200 which includesvarious values of a face vector for the expressions: neutral, surprise,shock, displeased, and disgust. The top row of the table 1200 showsillustrations of the expressions visually. An emotion can be associatedwith one or more facial expressions. Each facial expression can berepresented by a face vector. The face vector can include a plurality ofparameters for controlling a virtual character (e.g., by deforming amesh of the virtual character).

In the example shown in FIG. 12A, the plurality of parameters in theface vector includes two parameters for left and right eye browmovements (L.BrowUp, R.BrowUp), one parameter for Jaw (JawDrop), oneparameter for eyes (EyesOpen), and one parameter for lip corner(LipCorner), etc. The parameters of the face vector are also sometimesreferred to herein as variables, components, or dimensions. As willfurther be described herein, each parameter can also correspond to aface slider (e.g., an adjustment of the face slider will adjust thecontrol value of the corresponding parameter in a face vector).

A control value can be associated with each parameter in the facevector. The control values are typically numbers in a range from, forexample, 0 to 1, or −1 to +1, or some other numerical range. Withreference to the example shown in FIG. 12A, the neutral expression isassociated with a face vector in which the control values for L.BrowUp,R.BrowUp, JawDrop, and LipCorner are all 0.0, while the control valuefor EyesOpen is 0.5. By adjusting the control values for the parameters,the virtual character can be animated to show different facialexpressions. With continued reference to FIG. 12A, to animate thevirtual character to show Surprise, the control values can be changed to0.45 for L.BrowUp, 0.5 for R.BrowUp, 0.35 for JawDrop, 0.75 forEyesOpen, while the control value for LipCorner remains at 0.0. Examplecontrol values for other facial expressions (e.g., Shock, Displeased,Disgust) are also shown in FIG. 12A.

Each parameter of a face vector can be associated with a blendshape usedto animate the virtual character. By adjusting the control value for aparameter, the animation rig can adjust one or more vertices in a meshfor the virtual character.

FIG. 12A shows just the first five parameters of the face vector andtheir associated control values for five different facial expressions.In various other examples, the variables for controlling the facialexpressions can also be defined differently. As described above, theface vector can be any length (e.g., 137 in one embodiment). The lengthof the face vector can be set by the particular rig used for avataranimation. For example, a rig with more parameters may correspond to aface vector with a longer length (due to more dimensions in the facevector), whereas a rig with a smaller number of parameters maycorrespond to a face vector with a shorter length.

With reference to FIG. 12A, each row after the top row 1210 canrepresent one parameter across a set of expressions. The number withineach cell represents the control value for the corresponding parameterto achieve the given expression. The control values can be the valuesfor the corresponding FACS sliders. The control values can alsorepresent weights of the blendshapes associated with the variables. Forexample, when the avatar is in a neutral state, the value of thevariable for the lip corner is 0.0 representing the default location ofthe lip corner (e.g., no deformation to vertices of the mesh around thelip corner). However, if the avatar has a displeased facial expression,the control value of the lip corner variable can increase (e.g., to 0.45in FIG. 12A), and if the avatar transitions to a disgusted facialexpression, the control value of the lip corner variable can increaseeven more (e.g., to 0.8 in FIG. 12A). Thus, the visual expression of thelip corner (as shown in the row 1210) appears different between theneutral, displeased, and disgusted expressions. Similar considerationsapply to other component values of the face vectors.

Some control values can have values that range between positive andnegative values. As a result, the variables can support movements inboth directions (e.g., up and down, left and right, etc.). For example,a FACS slider of an eye brow can move up when the expression issurprised or shocked, and can move down when the expression isdispleased or disgusted.

As described herein, a rigging control system can automatically adjustcontrol values of the face vector to cause the avatar to be renderedover a range of expressions (or emotions corresponding to theexpressions or groups of expressions).

Examples of Mapping Vectors of Facial Expressions

FIG. 12B illustrates an example of a map 1250 of facial expressions.Each facial expression can correspond to a face vector (e.g., asillustrated in FIG. 12A), and an expression can be mapped to acombination of one or more facial expressions (e.g., a happy expressioncould correspond to 90% smile expression plus 10% surprised expression).The map 1250 can include a reference expression (which may be a neutralexpression). In this example, the map is largely two-dimensional (2D),but in other examples, the map could be three dimensional. For example,a 3D map could have the reference (e.g., neutral) expression at thecenter of a cube, with eight different expressions at the corners of thecube. Further details regarding the construction of the map 1250 areprovided below.

Expressions can progress as multiples of each other in themulti-dimensional space of variables. The face vectors of similar facialexpressions can lie along the same arm or direction in thismulti-dimensional map measured relative to the neutral expression. Forexample, vectors for happy and joyful can be in the same directionbecause these two facial expressions represent similar emotions but aredifferent in magnitude. A face vector may have a relative angle withrespect to another face vector where the differences of correspondingfacial expressions are more than a difference in intensity. For example,a happy vector and a sad vector can be positioned with an angulardifference. The angular difference between two face vectors can be inrange, such as, e.g., 5 degrees, 10 degrees, 20 degrees, 30 degrees, orany other degrees between 0 to 360 degrees or from −180 degrees to 180degrees, depending on the dissimilarities between the two face vectors.

In some implementations, it may be convenient (although not required) todescribe face vectors relative to the reference vector, which will bedescribed as the neutral face vector for convenience (but withoutlimitation). A delta vector for an expression is the face vector of theexpression relative to the neutral face vector. A delta vector can bethe difference between the neutral face vector and the expression facevector. This permits the facial expression to be represented as a change(e.g., the delta vector) relative to the neutral vector for the neutralexpression. Thus, the neutral expression can serve as an origin at thecenter of the map, and the facial expressions can be arrayed around thisorigin based on the geometric relationship among the delta vectorscorresponding to these expressions (e.g., lengths of the delta vectorsand angular relationships between the delta vectors). Such anarrangement of facial expressions and their corresponding delta vectorsis shown in FIGS. 12B and 12C.

For example, if the neutral vector is subtracted from the happy vector,a happy delta vector can be obtained. As another example, if the neutralvector is subtracted from an ecstatic vector, an ecstatic delta vectorcan be obtained. With reference to FIG. 12A, the delta vectors for thesurprise, shock, displeased and disgust vectors with respect to theneutral vector can be calculated using the following formulae 1A through1D, where each column in the table 1210 represents a face vector for thecorresponding expression.

=

−

  (1A)

=

−

  (1B)

=

−

  (1C)

=

−

  (1D)

The delta values for the expressions can represent the relativerelationships of the expressions (e.g., the intensity of the expressionsrelative to each other). For example, the ecstatic delta vector may belarger than the happy delta vector by a certain amount (e.g., the lengthof the ecstatic delta vector could be 3 times of that of the happy deltavector), which mathematically shows that the ecstatic expression is amore extreme version of happy. The length of a vector or a delta vectorcan be calculated according to the Euclidean or L2-norm, as describedbelow with reference to formula 2A (below). For simplicity, a facevector representing an expression may be referred to by the name for theexpression, e.g., a face vector representing the expression for“surprise” may be referred to as the “surprise vector” and a delta facevector for “surprise” may be referred to as the “surprise delta vector”and so forth.

The layout of the map 1250 can be mathematically derived by subtractingthe neutral face vector from each expression vector to generate anexpression delta vector. Expressions may be organized onto the map 1250based on relationships between the dot products of the deltas.

The vectors (or delta vectors) of different facial expressions may havedifferent directionalities. For example, a happy vector will have adifferent directionality from an angry vector (which may be insubstantially the same direction as a vector representing annoyance orrage). A fear vector (which may have substantially the same direction asapprehension and terror) would have yet another directionality from thehappy vector and the anger vector. The relative directionality of twovectors can be determined using vector algebra principles, for example,the angle between two vectors or delta vectors can be calculated usingthe scalar dot product. In various embodiments, two vectors may be insubstantially the same direction if the angle between the two vectors isless than 15 degrees, less than 10 degrees, or less than 5 degrees. Invarious embodiments, two vectors may be in substantially the oppositedirection if the angle between the two vectors is greater than 165degrees, greater than 170 degrees, or greater than 175 degrees (whilebeing less than or equal to 180 degrees, which represents the vectorsbeing directly opposite to each other).

For example, the delta vectors between an expression specific vector andthe reference expression vector can be used to calculate the relativedistance between the reference expression vector and the expressionspecific vector. The relative positions of two expression specificvectors (e.g., happy and disgust) on the map can be determined based onthe dot products of the delta vectors of the two expression specificvectors (each with respect to the reference expression vector).

As an example of generating the map, each face vector or each deltavector (e.g., with respect to the neutral vector) can be unitized (e.g.,normalized with respect to a length of 1). As an example of normalizinga delta vector for an expression, a length of a delta vector can firstbe calculated, e.g., using the formula (2A) below, which is theEuclidean or L2-norm:

∥{right arrow over (Δexpression)}∥=√{square root over (Σ_(i=1)^(n)expression_variable_(i) ²)}  (2A)

where ∥{right arrow over (Δexpression)}∥ represents the overall lengthof an n-dimensional delta vector of an expression (or an emotioncorresponding to one or more facial expressions) andexpression_variable_(i) represents a variable in the delta vector forthe expression. The value of each variable can be divided by the overalllength of the vector to obtain the unitized delta vector for anexpression.

The length of a vector can represent the strength of an expression (oremotion). A more extreme expression can have a longer length, whereas aless extreme expression can have a smaller length as shown in theformulae (2B-i) and (2B-ii) below.

∥{right arrow over (ΔSurprise)}∥<∥{right arrow over (ΔShock)}∥  (2B-i)

∥{right arrow over (ΔDispleased)}∥<∥{right arrow over(ΔDisgust)}∥  (2B-ii)

The dot product of unitized delta vectors of expressions can be taken todetermine the angular distance between the two delta vectors. Forexample, the dot product of two vectors can be calculated using theformula 2C-i below.

{right arrow over (Δexpresston_A)}·{right arrow over(Δexpresston_B)}=Σ_(i=1) ^(n)expression_A _(i) expression_B ₁  (2C-i)

where {right arrow over (Δexpresston_A)} and {right arrow over(Δexpression_B)} represent unitized delta vectors or delta vectors ofexpressions. Once the dot product is calculated, the angle θ between thetwo vectors can be calculated as shown in formula 2C-ii below, wherecos⁻¹ is the arccosine function. The angle θ can represent the relativeangular positions between the expression A vector and the expression Bvector.

$\begin{matrix}{\theta = {\cos^{- 1}\left( \frac{\overset{\rightharpoonup}{\Delta expression\_ A} \cdot \overset{\rightharpoonup}{\Delta expression\_ B}}{{\overset{\rightharpoonup}{\Delta expression\_ A}}\mspace{14mu} {\overset{\rightharpoonup}{\Delta expression\_ B}}} \right)}} & \left( {2C\text{-}{ii}} \right)\end{matrix}$

The output of the dot product is a number describing alignments (e.g.,similarities or dissimilarities) of expressions. Further, the length ofa vector is the square root of the dot product of the vector with itself(which is equivalent to formula 2A). For example, as shown in theformulae (3A-i) and (3A-ii) below, the dot product of similarexpressions is close to 1. In formula (3A-i) and (3A-ii), unit indicatesthe vector has been unitized.

unit({right arrow over (ΔDispleased)})·unit({right arrow over(ΔDisgust)})≈1.0  (3A-i)

unit({right arrow over (ΔSurprise)})·unit({right arrow over(ΔShock)})≈1.0  (3A-ii)

Opposite expressions (or emotions), however, may have a dot productcloser to −1, indicating that the delta vectors point in roughlyopposite directions on the map 1250. As shown in the example formula 3B,the dot product of the unitized delta vector for surprise and theunitized delta vector for displeased is roughly −1.

unit({right arrow over (ΔSurprise)})·unit({right arrow over(ΔDispleased)})≈−1.0  (3B)

A mapping of expressions can be generated based on the lengths and dotproducts calculated according to the foregoing vector analysisprinciples. FIGS. 12B and 12C illustrate an example of a map 1250 ofexpressions. The map 1250 has a reference expression (e.g., neutral)placed in the middle of the map. A primary vector 1276 (e.g., apensiveness vector) can be identified and placed at a given direction(e.g., placing the pensiveness vector to the north of the neutralvector). The primary vector can be identified randomly, or with anystructured rules.

The rest of the expressions can be placed relative to the primary vectorbased on the angular relationship and the distances between the rest ofthe expressions. For example, the vector dot product can be used todetermine the angular relationship between delta vectors as shown informula 2C-ii, and the distance from the central expression can bedetermined based on the length of a delta vector for that expressionusing the formula 2A. For example, the dot product can be used todetermine an angle at which that expression should be positionedrelative to the primary vector. If the dot product between the primaryexpression and another expression is near one, the primary expressionand the other expression can be placed in the same general direction. Ifthe dot product is close to 0, then the primary vector and the otherexpression are roughly perpendicular to each other. If the dot productis close to −1, the primary expression and the other expression areplaced at the opposite sides of the map 1250.

Even if expressions are aligned, some of the expressions are strongerthan others. As described above, the length of a vector indicates thestrength of an expression. For example, a more extreme expressiontranslates to a longer length (e.g., the vector 1274 has a longer lengththan the vector 1272 shown in FIG. 12C). The map 1250 can place moreextreme expression further away from the center, neutral expression.

With reference to the FIG. 12B, different expression vectors can beprojected into a two-dimensional space, as shown in the map 1250. Themap 1250 can have the neutral expression as the central expression. Themap 1250 can include a plurality of arms 1252 where each arm comprisessimilar expression with different intensities. The relative positionsbetween each expression can be determined with respect to a primaryexpression. The primary expression can be any one of the expressionslisted on the map 1250. As an example, the primary expression can be“fear”.

Deltas between each expression and the neutral expression can be takento generate delta vectors (e.g., where subtraction or addition may beperformed between an expression vector and a neutral vector). FIG. 12Cillustrates examples of the delta vectors 1276, 1274, and 1272. Thedelta vector 1276 can be for pensiveness; the delta vector 1274 can befor yawn; and the delta vector 1272 can be for drowsiness, in thisexample. The delta vectors (or the unitized delta vectors) can be usedto calculate the dot products between the primary vector (e.g., thevector 1276) and other vectors (such as, e.g., vectors 1274, and 1272)to determine the relative positions on the map 1250 (e.g., relativeangular positions in a 2D map). As shown in FIG. 12C, an angle θ can becalculated for the angle between the vector 1272 and 1276 which candetermine the angular position of the vector 1272 relative to the vector1276. The vector 1274 is at the same angle θ as the vector 1272 but isat a greater distance from the origin (e.g., the neutral expression),because the drowsiness expression represented by the vector 1274 is moreextreme than the yawn expression represented by the vector 1272 (andtherefore has longer length). As another example, the dot product of theunitized fear vector and the unitized worry vector can be close to 1,which suggests that the fear vector and the worry vector should berepresented in the same arm of the map 1250. The dot product between theunitized fear vector and the unitized pain vector may be around 0.4which indicates that the direction of the pain vector can be at an acuteangle (of about 33 degrees) with respect to the direction of the fearvector.

In addition to or as an alternative to the map shown and described withreference to FIGS. 12B and 12C, the map of expressions can have otherornamental appearances. FIG. 12D illustrates another example of the map1250 which has a more rectangular appearance than the wheel-likeappearance of the map shown in FIGS. 12B, 12C. In the example map shownin FIG. 12D, the neutral expression is shown at the bottom of the map,with arms 1252 extending vertically upward. In this example, theemotions shown in each arm can share a common expression or be connectedto the neutral expression.

The map designs shown in FIGS. 12B, 12C, and 12D can be part of agraphical user interface, which can be presented to the user by thewearable system 200 described herein. The appearances of the map ofexpressions shown in FIGS. 12B, 12C, and 12D are examples, and theexpressions can be mapped differently than shown (e.g., in maps havingpolygonal shape, circular shape, linear shape, 3D shape, etc.).

Animation Blendspace with 2D Projections of Expression

The map 1250 can be used by a rigging control system in an animationblendspace to provide realistic expressions of a virtual character. Inanimation, only a small subset of possible expressions or emotions maybe created as defined vectors. These defined vectors can correspond tothe faces (e.g., expressions) as shown in the map 1250. Otherexpressions can be derived from the animation blendspace by blending anumber (e.g., 2, 3, 4, 5, 6, or more) of closest expressions to a blendcursor. For example, with N=3, an animation blendspace can comprise aset of non-overlapping 2D triangles where each vertex of each trianglerepresents an animation.

FIG. 12C illustrates an example of animation blendspace where N=3. Inthis example, a triangle 1280 is formed among three expressions: slightsmile 1296, smile 1292, and fake smile 1294. A blend cursor 1285 canreside within the triangle 1280 and indicate a proportional amount ofthe three animations at the vertices of that triangle that are used inrendering the facial expression. The proportions can be based on thedistance from the blend cursor 1285 to each of the 3 vertices. Theproportions can be used to define the weights of the animations forderiving expressions that are not included in the explicitly definedvectors on the map 1250, thereby permitting the rigging system tointerpolate (or morph) between expressions that are explicitly defined.The movement of the blend cursor 1285 is not restricted to a triangle,The blend cursor 1285 can move to anywhere on the map 1285 which wouldcause the rigging control system to generate a facial expression basedon the blend cursor's 1285 current position and N facial expressionsaround the cursor (e.g., N=3 for a triangle). For example, where theblend cursor 1285 lands on a facial expression that is explicitlyprojected onto the map (e.g., the sad, worry, happy expressions, etc.),the rigging control system may cause the avatar to show the facialexpression. Where the blend cursor 1285 does not land on a particularexpression on the map, the rigging control system can generate a facialexpression by blending N nearby animations, based on, e.g., the blendcursor's 1285 relative positions with respect to the vertices of atriangle (or other shapes) associated with animation blendspace.

In some situations, unnatural or odd facial expressions may result ifthe layout of the expressions in the 2D space is not properly selected.Incorrect facial expressions are undesirable as it breaks the realism ofthe virtual character. Advantageously, techniques for generating the map1250 can reduce or minimize the likelihood of generating unnaturalfacial expressions and can create realistic intermediate expressions(e.g., in-between face vectors or blendshapes).

As described with reference to FIGS. 12A and 12B, the map can begenerated by mathematically deriving the blendspace layout viasubtracting the neutral expression from each key expression (e.g., thosethat will be part of the map 1250) to generate an expression delta andorganizing the expression deltas based on vector analysis principles(e.g., the length of the deltas and the angle between the deltas usingthe dot products of the deltas). This technique can result in anarrangement which improves or optimizes the positions for the Nexpressions used to determine the blendspace (e.g., 3 expressions forthe triangles described above).

The map 1250 generally is different from other representations ofexpressions or emotions (e.g., Plutchik's wheel of emotions), which ifused directly, can lead to unnatural animation results. For example, themap 1250 can invert the emotions in the Plutchik wheel of emotions tohave a neutral zone at the center and have the stronger emotions towardthe outer rim of the map 1250. This can advantageously allow theblending of expressions to have a common neutral position at a centrallocation. In addition, if each facial expression is positioned relativeto a neutral facial expression, a display can render a relativelyneutral facial animation and then add back the current expression (via adelta vector), which would provide a layer of motion to make the faceappear natural instead of being frozen (e.g., at an expression) like awax work.

Example Processes of Generating a Map of Facial Expressions

FIG. 13 illustrates an example process 1300 of generating a map offacial expressions for animation blendspace. The example process 1300can be performed by a wearable system 200 (such as, e.g., by the remoteprocessing module 270) or by the computing device 10 shown in FIG. 19.The map can comprise 2D projections of facial expressions. The map maybe similar to the map 1250 shown in FIG. 12B. The map can be used tocreate animation blendspaces for generating facial expressions that arenot explicitly shown on the map.

At block 1310, a set of facial expressions can be identified. The set offacial expressions may include key facial expressions which can be mixed(e.g., via animation blendspace) to derive other facial expressions. Theset of facial expressions can be projected into a map (which may be in ashape of a wheel, rectangle, or other 2D or 3D shape). The layout of thefacial expressions in the map can be improved or optimized for animationblendspace to render realistic facial expressions for a virtualcharacter. The map can be 2D (as in FIG. 12B) but may be 3D or a higherdimensionality in other implementations. The map can have a differentnumber of expressions or arms as compared to the illustrative map shownin FIG. 12B.

At block 1320, a first delta vector can be calculated by calculating thedelta between the first vector of the first facial expression and areference vector. The reference vector may be a neutral vector or anyother vector. The reference vector can be used to calculate the deltavalue with respect to other vectors that will be plotted. The deltavalue can determine the distance between a vector and the referencevector on the map, as described herein. The vector for the firstexpression can be set as the primary vector for plotting the othervectors to the map (e.g., the vector that is displayed vertically upwardsuch as North on a compass). As described in the later blocks, theprimary vector can be used to determine the angular relationships of thevectors on the map (e.g., a vector is at a certain degree from theprimary vector).

At block 1330, the first length of the first delta vector is calculated.The first length can be calculated using the formula (2A) described inthe preceding section.

At block 1340, the second delta vector can be calculated by taking thedelta between the second vector of the second facial expression and thereference vector. The second delta vector can be calculated usingsimilar techniques as those for calculating the first delta vector.

At block 1350, the second length for the second delta vector can becalculated. The second length can also be calculated using the formula(2A) described herein.

At block 1360, an angular relationship between the first and the seconddelta vectors is determined so that the second delta vector can beoriented on the map relative to the first delta vector. For example, adot product of a unitized first delta vector and a unitized second deltavector can be calculated. The dot product value is the cosine of theangle between the two delta vectors and can indicate the relativeangular positions between the first facial expression and the secondexpression in the map for the animation blendspace.

The process 1370 can perform the same analysis for other facialexpressions in the set of facial expressions. At block 1370, the processcan determine whether there are any remaining facial expressions in theset of facial expressions. If there any remaining facial expressionswhose positions on the map is unknown, the process 1300 proceeds to theblock 1380, where the processes of block 1340 through 1360 can beperformed on a remaining facial expression.

If the positions of all facial expressions are known, at block 1390, amap for animation blendspace can be generated. The map can be generatedwhere each arm 1252 can share a common neutral expression or beconnected to a neutral expression. As one example described withreference to FIGS. 12B, 12C, the neutral expression may be positioned inthe middle of the map with each arm 1252 extending outward toward adirection. In other examples, the neutral expression can be positionedelsewhere in the map (e.g., the neutral expression is at the bottom ofthe map shown in FIG. 12D), and the map is not necessarily limited to awheel or circular shape or a rectangular shape. The first facialexpression may be set at a random direction (or defined direction) fromthe neutral expression (e.g., in the North direction as in a compass).The distance between the first facial expression and the neutralexpression can be determined based on the length of the first deltavector.

The positions of other facial expressions in the set of facialexpressions can be based on the angular relationships (e.g., from thedot products between the first delta vector and the delta vectors of theother facial expressions). The lengths of the delta vectors for theother expressions can define the distance between the other expressionsand the neutral expression on the map (e.g., how far away from thecenter the expressions are placed, which correlates with the strength ofthe expression).

The blocks in the process 1300 do not have to be performed in a certainorder. For example, block 1360 can be performed before the block 1350 orat the same time as the block 1350.

In some embodiments, a wearable system (e.g., the system 200) or acomputing device (e.g., the device 10) can render the map 1250 to a userof the system. The user may be able to provide input (e.g., via a totem466) to the rigging control system by moving a cursor around in the map1250 and selecting an expression (see, e.g., FIG. 12C showing the blendcursor 1285 and the blendspace 1280 for the map 1250). The riggingcontrol system can then cause an avatar to be rendered (remotely or onthe same computing device) based at least partly on this user input.This may be advantageous when a user wants his or her avatar to displayan expression that is different from the user's actual expression in thereal world. Thus, the user can navigate within the map to select theexpression or expression transitions that the user would like his or heravatar to display.

Examples of Transitioning Facial Expressions

A virtual character's expression can change from time to time (e.g., asthe blend cursor is moved through the animation blendspace or throughthe map 1250, in response to a user's interaction, or in response to anevent in the virtual character's environment). However, during suchtransitions, the whole face would be changed from one expression toanother at once. For example, when an avatar's expression istransitioned from sad to happy, all regions of the avatar's face wouldchange simultaneously. This results in unnaturalness in the avatar'sfacial expression as a real human face does not change from oneexpression to another all at once. The expressions of a real human facetend to sweep across the face. For example, during the transition fromsad to happy, the eyes may start to show an expression indicatingsmiling before the mouth changes to smile.

An improved transition system can be implemented to reduceunnaturalness. This transition system can specify a starting facialexpression, an ending facial expression, and a sweep direction for eachpoint in time. A sweep speed may be specified to indicate how quickly(or how slowly) the transition from the starting facial expression tothe ending facial expression occurs. The starting facial expression cancorrespond to a first vector and the ending facial expression cancorrespond to a second vector. The sweep direction can control whichvariable of a face vector will be changed from a value associated withthe first expression to a value associated with the second expression.The sweep speed can control the rate of this change. For example,assuming the sweep direction is downward (e.g., from the top of the faceto the bottom of the face or from the nose to the mouth, etc.), thesliders associated with the eye region can be moved before a sliderassociated with the mouth is updated to move from the starting facialexpression to the ending facial expression. Because this transitionsystem implements a sweep, delays can be added to variables of thevectors based on the sweep direction or the sweep speed. As a result,the change of values for certain variables may not occur immediately inresponse to a change of expressions and thus may appear more realistic.Further details are provided below in the context of an example springsystem that can be associated with the sliders.

The parameters of the transition system can be altered to change thedirection of the propagation (which is also referred to as sweepdirection) or the sweep speed. As an example, the sweep direction can beradial such that the expression change can start at a point (e.g., thenose) and propagate outward from that point. The transition system canexecute differently depending on the starting and ending expressions.For example, the sweep direction or speed can be different where thetransition is from happy to angry versus from angry to outrage. Thus,the sweep direction can be, e.g., from an upper face region to a lowerface region, from a lower face region to an upper face region, from acenter face region moving radially outward, and so forth. The sweepspeed can reflect the typical time humans change their expression, e.g.,in a range from about 50 ms to 1000 ms.

Advantageously, the techniques of the transition system described hereincan be dynamic and allow transitions from an expression to any otherexpression at any point in time. The transition techniques can allowseamless flow from one expression state to another, and enable theexpression to sweep across the face. The transition can start at anypoint and finish at any ending point (even though another transition isstill in progress), and the direction or speed of the sweep can bedifferent or randomized for every play-through (of the same transition),which can advantageously provide more realistic expressions andappearances for virtual characters. Further, the transition system herecan quickly and easily derive intermediate expressions (or in-betweenface vectors) based on the map for the animation blendspace, because theexpressions can be projected into the map as multiples of each other(e.g., based on the distance to the neutral vector) in each direction(e.g., as shown in the arms on the map 1250).

This is in contrast with traditional pre-rendered animation technologiesfor sweeping expressions across the face. The traditional pre-renderedanimation usually pre-selects two expressions—a start expression and anend expression—and then blends the two in order to create an animatedcharacter. The pre-animated facial expression sweep has a fixed startingpoint and a fixed end point, and the animations are constant for eachplay-through. Further, because transition is a pre-rendered animation,it has to be played from beginning to end before the virtual charactercan transition to another expression. As a result, the virtual charactercannot change expression or perform another action during thetransition.

Embodiments of the present system permit dynamic transitioning that doesnot have the limitations of traditional pre-rendered animationtechniques. For example, the system may be transitioning from expressionA to expression B. Before completion of the transition, the expressionof the avatar changes so that the avatar should be rendered withexpression C, rather than expression B. The system can naturally anddynamically change the sweep direction (or speed) so that the transitionmoves to expression C (rather than expression B). As discussed,traditional techniques require the system to complete the transition toexpression B before then transitioning to expression C, which can appearunnatural and may cause a noticeable delay between the virtualcharacter's reaction time and environment.

FIG. 14A illustrates an example of transitions of expressions of avirtual character where the whole face changes from one state to anotherat the same time. FIG. 14A illustrates 4 expression states at differentpoints in time: neutral state at state 1412, sad state at the state1414, a worried state at the state 1416, and a surprised state at thestate 1418, for an avatar's face 1400. In this example, the face 1400 isdivided into 3 regions: regions A, B, and C for simplicity ofillustrations. The region A corresponds to the upper face, the region Bcorresponds to the nose region, and the region C corresponds to thelower face. In other examples, a different number of facial regionscould be used, e.g., 2, 4, 5, 6, or more. In other examples, a facialregion may correspond to an individual facial control.

At time 1, the entire face is in the neutral state 1412 (e.g., regionsA, B, and C are all in the neutral state). The face can be changed tothe sad state 1414 at time 2. However, this transition would causeregions A, B, and C to be changed from neutral to sad simultaneously asshown by the table 1420. The face can further be transitioned from thesad state 1414 to the worried state 1416 at time 3 and from the worriedstate 1416 to the surprised state 1418 at time 4. Similar to thetransitions from the state 1412 to the state 1414, the transitions fromthe state 1414 to the state 1416 and from the state 1416 to the state1418 occur with all regions A, B, and C of the face changingsimultaneously. As a result, the virtual avatar may appear unnaturalwhen its facial expressions have changed, because the entire facechanges at the same time.

FIGS. 14B and 14C illustrate an example where the rigging control systemincludes a transition system that dynamically updates a virtualcharacter's facial expressions in a swept fashion. As a result, theexpressions of the face can be constantly updating without needing towait for the complete of a transition. Different regions of the face cantransition differently, e.g., with different speeds and with differentexpressions.

The examples shown in FIGS. 14B and 14C assume that the sweep directionis steady (e.g., upward in FIGS. 14B and 14C), although this is assumedfor illustration and is not a limitation. In these examples, theavatar's expression can change from neutral, to sad, to worried, tosurprised, and backwards. Each of the three facial expressions can sweepacross the face (in the sweep direction) in succession. If the speed ofthe sweep is matched with the rate of the change of the expression, theface may at one point have a sad mouth, a worried nose, and surprisedeyes (see face 1448 at time 8 in FIG. 14B). In situations where thespeed of sweep is slower than the rate of change of expressions, aviewer may not be able to perceive an earlier facial expression on someportions of the face. If the speed of sweep is faster than the rate ofchange of expressions, the whole face (or at least a portion thereof)can have the previous expression before the new expression starts to beshown on the face.

FIG. 14B shows an example of the face 1400 from time 1 through time 8.Note that the face transition between time 1 and time 8 in FIG. 14Bgenerally corresponds to the face transition between time 1 and time 4in the traditional system shown in FIG. 14A. At time 1, the entire faceis at a neutral state 1432. As shown in the table 1450, the regions A,B, and C are all in the neutral state 1432 at time 1. At time 2, theface 1400 is being transitioned in to a sad state. However, because aswept transition mechanism is implemented, the region C at the bottom ofthe face is changed to sad at time 2 whereas regions A and B remainneutral at time 2 (due to the upward sweep direction). As a result, atstate 1434, the lower face shows a sad expression whereas the upper faceand nose region remain neutral.

At time 3, a transition to a worried expression is triggered. But thetransition to the sad state has not yet completed. Advantageously,rather than waiting for the transition from neutral to sad to complete,at time 3, the region C can be automatically changed to a worriedexpression even though the transition to the sad expression across theremainder of the face has not yet been completed. As shown in the state1436, the lower face (region C) has a worried expression at time 3because the worried expression is triggered. However, region B istransitioned from the neutral to sad, because the sweep has reachedregion B. At time 3, the sweep has not yet reached region A (at the topof the face), and region A remains in a neutral expression.

At time 4, however, a surprised expression may be triggered. Asdescribed with reference to state 1436, the region C can show asurprised expression at state 1438 because the seep is upward and beginsin region C. Whereas region B can show a worried expression (to continuethe transition from sad to worried) and region A can show a sadexpression (to continue the transition from neutral to sad, because thesweep has now reached the top part of the face). Thus, at time 4, the 3regions A, B, C of the face each rendered with a different facialexpression.

At time 5, there is no trigger for a new expression, as a result, atstate 1442, the transition to the surprised expression continues tosweep up on the face (as shown by the change in expressions in regionB). Transition from the sad to worried can continue (as shown by thechange in expressions in region A) and complete at time 5. There is alsono new trigger at time 6. As a result, when transitioning from state1442 to 1444, regions C and B remain in the surprised state, and regionA transitions from worried to surprised. All three regions A, B, and Care now in the surprised expressive state at time 6. This facialexpression corresponds to the state 1418 in FIG. 14A in which the entireface is surprised. However, the example transition shown in FIG. 14Bsweeps across the face and appears more natural and realistic than theabrupt transitions shown in FIG. 14A.

Continuing with this example, at time 7, a worried expression istriggered for the avatar. As a result, the expression in region C ischanged to worried whereas the expression in the remaining regionsremain surprised due to the upward sweep as shown in state 1446. At time8, a sad expression is triggered and the expression in the region C ischanged to sad. In state 1448, the upward sweep for worried continues inregion B while region A remains in the surprised state.

With reference to FIG. 14C, at times 9 and 10, there are no newtriggers, and the lower region C remains in the sad state. The upwardsweep for the sad expression and the worried expression continues. Thetransition to worried completes at state 1462 whereas the transition tosad completes at state 1464. Once the transition to an expressioncompletes, the expression can stay until a new trigger to change to anew expression is detected. The newly triggered expression then beginsto sweep across the face.

At time 11, a trigger for the neutral expression is detected. Forexample, after an avatar has a certain expression for a period of time,the intensity of the expression may decrease (e.g., the avatar has lostinterest of an object or the avatar's emotional or expressive state hascooled down) and return to neutral. At the state 1466, the bottom of theface (region C) appears to be neutral whereas the expressions in theregions A and B remain unchanged compared to the state 1464. No newtriggers are detected for times 12 through 16. As a result, the neutralexpression can gradually sweep through the face as shown in states 1466through 1472 and remain at the neutral state as illustrated in states1474 through 1478 and the table 1480.

Although the examples shown in FIGS. 14A-14C divide the face into threeregions, in various example situations, the regions of the face can bedivided differently. For example, the regions could be arrangedhorizontally (rather than vertically as shown) or arranged in ringsextending away from a central portion of the face (e.g., the nose). Eachregion may also be defined by one or more face sliders. Further, inaddition to or in alternative to dividing the face into regions, similartransition techniques (or delay mechanisms) can be applied to variablesof the face (e.g., the face sliders described with reference to FIG.11).

Although the sweep direction is set as upward in FIGS. 14B and 14C,advantageously, in some embodiments, the sweep direction can berandomized to provide more vivid facial expressions. To enablerandomization of the sweep direction, the sweep direction can beprogrammed independently from the triggering events of changes in facialexpressions or emotions. As a result, one expression can be changed toanother via a number of sweep directions. For example, to change fromworried to happy, the facial expression change can start at the chin andsweep up where a worried mouth turns into a smile followed by worriedeyes turning into smiling eyes. Alternatively, the facial expressionchange can start at the forehead; sweep down with the eyes changing fromworried to smiling eyes; and then the mouth changes form worried tosmiling. Many variations are possible, and the rigging system can use arandom number generator to select how the regions are swept. Thistechnique will generate avatar facial transitions that are differenteach time the avatar makes the transition. Rather than always making atransition (e.g., from neutral to smiling) in exactly the same way,which leads to a robotic appearance in the uncanny valley, the riggingsystem can randomize the transitions to make the avatar appear morelifelike and less robotic.

In some situations, a sweep direction change accompanying an expressionchange can cause the virtual character to flip flop facial expressionswhich can cause an unnatural result. To get around this problem, thesweep direction may be set to change when the expression is notchanging. To determine whether the expression is changing, thetransition technique can calculate a historical velocity of the blendcursor (e.g., the cursor 1285) on the wheel of expression. Theexpression remains the same when the historical velocity equals zero.

Example Processes of Transitioning Facial Expressions

FIG. 15 illustrates an example process for transitioning expressions ofa virtual character. The example process 1500 can be performed by thewearable system 200 (e.g., modules 260, 270 or the avatar processing andrendering system 690) or the computing device 10 described withreference to FIG. 19. The example process 1500 can be performed duringreal-time while a virtual character is interacting with a viewer or theenvironment.

The virtual character may have a current state of facial expression. Thecurrent state of facial expression can be a neutral expression or thelast expression in which the virtual character has expressed. At block1510, the process 1500 can identify a first trigger of a firstexpression change from a first expression (which may be the currentstate of the facial expression) to a second expression. The trigger maybe based on a viewer's interaction, an event of the environment, orcertain predefined criteria (e.g., time elapsed since the lastexpression), etc. For example, a user's action may cause the virtualavatar to appear happy, angry, sad, etc. As another example, a loudsound can cause the virtual character to show a scared or surprisedfacial expression. As yet another example, the avatar of a user canreflect the user's facial expression, which can be obtained, e.g., froman external camera in the environment or from the inward-facing imagingsystem of a wearable device. For example, when a user is angry, theavatar of the user can also have an angry facial expression.

At block 1520, the process 1500 can identify parameters of the firstexpression change. The parameters can include a sweep speed or a sweepdirection associated with the first expression change. The sweep speedand direction may be associated with the dynamic transition mechanismfor implementing the avatar's expression change across the facedescribed with reference to FIGS. 14B and 14C. The parameters can alsoinclude regions of the face (e.g., regions A, B, C illustrated in FIGS.14B, 14C) across which the expression will be swept.

At block 1530, the second expression can be swept across the face of thevirtual characters based on the sweep speed and direction. For example,when the sweep occurs, a first region of the face can be identifiedbased on the sweep direction, where the expression in the first regioncan be changed from the first expression to the second expression. Forexample, where an avatar is changed from neutral to happy, the firstregion of the face can show a happy expression even though other regionsof the face may still show a neutral expression. The location and sizeof the first region can be determined based on the sweep speed ordirection. A fast sweep speed may cause a larger region to have thehappy expression at a given time than a slow sweep speed, because theexpression propagates across the face more quickly with a fast sweepspeed. The direction of the sweep can also affect which region of theface will have the happy expression.

At block 1540, a second trigger for expression change is detected. Thistrigger can cause the facial expression of the virtual character tochange from the second expression to a third expression (which mayinclude the original expression, such as, e.g., the first expression atblocks 1510 and 1520).

At block 1550, the process 1500 can determine whether the firstexpression change has been completed. The process 1500 can check whetherdifferent regions of the face (e.g., regions A, B, C) have completed theexpression change. The process 1500 can additionally or alternativelymake such determination by calculating or accessing a rate of expressionchange. This rate can be calculated based on the expression change fromthe first expression to the second expression and from the secondexpression to the third expression over a time period. The expressionchange may be driven by user input (e.g., a user adjusting the cursor1285 described with reference to FIG. 12C) or be external events orinfluences in the real or virtual environment (e.g., interactions amongavatars or users, interactions between an avatar and real or virtualcontent in the environment), etc.

The appearance of the avatar can depend on the rate of expression changeand can be used together with the sweep speed to determine the currentfacial expression(s). For example, if the rate of expression change isfaster than the sweep speed, the first expression change may not havebeen completed before the second expression change occurs. As a result,at block 1570, the process can continue with the first expression changeby sweeping the second expression across the remaining regions of theface while initiating the second expression change by changing theregions of the face that are already in the second expression to thethird expression. As an example, the process 1500 can apply a secondexpression to a first region of the face while apply the thirdexpression to the second region of the face.

In some situations, if the sweep speed is fast enough, the firstexpression change may have already been completed before the secondexpression change occurs. As a result, the full face may show the secondexpression before the third expression appears on the first region ofthe face. Thus, at block 1560, the process 1500 can initiate the secondexpression change by sweeping the third expression across the face usingparameters associated with the second expression change.

Animating A Virtual Character with Realistic Physics

If the face is animated by adjusting face vector component values oradjusting face sliders, sometimes the face may appear to be mechanical.To increase the naturalness of the facial movements, additionalphysicality can be added in a physics-based program to simulaterealistic physics based movements of the skin. For example, the cheeksmay bounce more than the nose because the cheeks are a less controlledand have softer body mass than the nose. Also, the physics basedsimulation can soften the entry to and exit from motion. For example,when eyebrows are raised the nature of their control muscles and theirweight can ease them into a motion as opposed to an abrupt, roboticjumping into the motion.

The physics-based program is typically implemented as a separatesoftware program apart from the rig. However, on a device with limitedcomputational power (e.g., a wearable device or a computing device 10which has limited processing capacity), this implementation mayintroduce delays or may render the physics-based program unsuitable forcertain implementations. Further, in many AR/VR/MR applications, therealistic physical movements may need to be rendered in real-time inresponse to a user's interaction or an event in the environment, whichfurther increases the computational requirements to implement thephysics based program.

To provide realistic physical movements for the face on acomputationally limited device or in real time, embodiments of theavatar control system may incorporate a spring system that can be tunedto mimic realistic facial motions (e.g., bounce of cheeks during asmile). For example, a tunable spring system can be added to some or allof the control values of the face vector (or face sliders) withoutneeding to build out an entire separate physics-based program for theface. The tunable spring system can operate in real time oncomputationally-limited hardware processors.

FIG. 16A illustrates an avatar face transitioning between twoexpressions: neutral 1612 and shock 1614. As described with reference toFIG. 12A, an expression can be represented by an n-dimensional facevector having a set of control values 1622 for controlling the face'smovements. The control values within the face vector can be differentfor each expression. For example, as seen in FIG. 16A, control valuesfor the neutral face vector (associated with a neutral facialexpression) are different from the control values for the shock facevector (associated with a shocked facial expression). As describedabove, in some implementations, the number n is 100 or more (e.g., 137)depending on the rig associated with the face vector.

To add physicality to transition the face from a first expression to asecond expression (e.g., from neutral to shock as shown in FIG. 16A),the tunable spring system can include a tunable control parameter forsome or all of the control values of the face vector to give theappearance of more realistic physical movements. Each slider can haveits own tunable spring to simulate real physical movements (e.g.,elasticity), because different parts of the face can behave differently.For example, if a virtual character transitions to a big smile, thecheek (which is fleshier and thus would result in more bounce), wouldhave a different movement than the nose (which is more rigid and thuswould result in less bounce or movement when touched). As will furtherbe described with reference to FIG. 16B, the tunable control for aslider may start to take effect when the transition from one expressionto another is triggered or after the control value of the variable towhich the tunable control is added has reached a threshold level.

Formulae 4A-4C illustrate an example of incorporating a tunable springsystem in a face parameter. As will further be described with referenceto FIG. 16B, the tunable spring system can be incorporated in a faceparameter to drive the movement of a portion of the face during thetransition from a control value to another (until the control value ofthe parameter settles on a target value of the desired expression).

In the formula (4A) below, a force for compressing or extending thetunable spring is calculated.

F=K×(P _(target) −P _(t-1))  (4A)

In this example, F represents the force exerted by the tunable spring, Krepresents a spring constant for the tunable spring associated with theface parameter, and (P_(target)−P_(t-1)) represents the displacement ofthe spring between its target (or equilibrium) value and the value (orposition) of the spring at time t−1 where P target is the target valuefor the face parameter (to achieve an expression) and P_(t-1) is thevalue (or position) of the spring at time t−1.

The force calculated from the formula (4A) can be used to calculate theacceleration (A_(t)) associated with the external force exerted by thespring at time t. The acceleration (A_(t)) which can be used tocalculate the velocity of the spring at time t (V_(t)) as shown informulae (4B-i) through (4B-iii) below.

$\begin{matrix}{A_{t} = \frac{F}{M}} & \left( {4b\text{-}i} \right) \\{{\Delta \; T} = {T_{t} - T_{t - 1}}} & \left( {4b\text{-}{ii}} \right) \\{V_{t} = {{V_{t - 1} \times D} + {\Delta T \times A_{t}}}} & \left( {4B\text{-}{iii}} \right)\end{matrix}$

where M is the mass being accelerated by the spring, D is a dampingconstant to simulate friction, V_(t-1) represents the velocity of thespring at time t−1, and ΔT represents the time interval between time tand time t−1. The time interval can be any interval specified by aprogrammer or a user (e.g., 10 ms, 1 ms, 0.5 ms, etc.). In this example,the damping constant D simulates the damping motion (in the physicalworld) by adding a drag to the velocity. Thus, the constant D may be inthe range of [0, 1]. With reference to FIG. 16B, the time between t1 andt2 or after t2 can be subdivided into smaller time intervals and thesesmaller time intervals may be used for calculations of ΔT.

The position of the spring at time t (which can correspond to thecontrol value of the face parameter at time t) can be calculated usingthe formula 4C below.

P _(t) =P _(t-1) +ΔT×V _(t)  (4C)

The values for V_(t) and P_(t) can be updated during a transitionbetween two facial expressions, starting from an initial position (e.g.,at time t=0) to a final target position.

Any or all of the spring parameters K, M, and D can be tuned in theabove formulae. As an example, where a face parameter corresponds to afleshier region of the face (e.g., a cheek), the value of K for thespring (associated with the face parameter) can be small. On the otherhand if the face parameter corresponds to a stiffer region of the face(e.g., the nose), the value of K may be larger. The mass M can be tuned,e.g., such that a heavy brow is represented by a larger mass M.

The value of a tunable spring control can move directionally with thecorresponding slider. The movement can be in 1D or 2D or 3D. Forexample, where the slider is a spreader (e.g., which expands in twodirections, such as x and y directions), the slider movement can be in2D space.

FIG. 16B illustrates graphs associated with tunable controls for facesliders. The graphs 1630, 1640, 1650 show three examples of how thevalue of the left eyebrow component of a face vector changes when afacial expression changes from a neutral expression to a shockedexpression (as shown in FIG. 16A, first row below visual expressions in1622) as a function of time. In this example, the value of the left browdimension equals 0 when the avatar is in the neutral expression, whereasthe value is 0.85 when the avatar is shocked. These graphs show threedifferent examples of transitioning the left brow dimension value (onthe vertical axis) from 0 (neutral) to 0.85 (shocked) over a time period(on the horizontal axis). Although these graphs show the behavior of thespring system for the left brow dimension slider, similar behaviorapplies for other face vector components to which a spring is applied.In the graphs 1640, 1650, the position as a function of time wascalculated by solving formulae 4A-4C.

In FIG. 16B, each of the graphs 1630, 1640, and 1650 have three regions.

The first region is between time 0 and time t1 during which the avatar'sexpression is neutral. The second region is between times t1 and t2,during which the avatar's expression is transitioning from neutral toshocked. During this period, the tunable spring control can be turned onand the value controlling the left eye brow may start to change. Thethird region is from time t2 onward where the avatar remains shocked. Inthis phase, the control value can reach a target value which may triggerthe physicality to be applied. The control value may asymptote to thetarget value (e.g., 0.85 for the left brow) and may (optionally) have adecaying oscillation around the target value. Thus, a tunable springprovides a way to make the transition between two slider values morerealistic and lifelike than an abrupt transition or a straight lineartransition.

The graph 1630 illustrates an example of how the value of the lefteyebrow parameter changes when no spring is added to the left eye browvariable and the transition is performed linearly. At t2, once thecontrol value reaches the targeted value of 0.85, the control value nolonger changes. As a result, the transition between neutral and shockedmay appear to have an abrupt start and an abrupt stop at the twovertical lines indicating t1 and t2, and thus give the eyebrow raise ofthe avatar a robotic or mechanical appearance.

The graph 1640 illustrates a scenario where a tunable spring is added tothe variable for the left eyebrow. The tunable spring can simulate thebehaviors of a physical spring. As a result of the tunable spring, thecontrol value (which can be calculated using the formulae (4A-4C)) cangradually increase nonlinearly between t1 and t2, oscillate around thetarget value after t2, and eventually settles on the target value.Further, the slope of the curve (which corresponds to the velocity inthe formula (4C-ii)) between t1 and t2 starts small (near 0), graduallyincreases, and then may gradually oscillate around and decrease back to0 as the transition completes. In contrast, in the graph 1630, the slopeof the curve instantly jumps from 0 to a constant which remains the samebetween t1 and t2, and then instantly jumps back to 0.

The behavior of the curve in the graph 1640 is similar to the behaviorof an underdamped spring system and may exhibit damped, oscillatoryringing after time t2 as the curve approaches the asymptotic targetvalue (of 0.85 in graph 1640). Depending on the type of facial movementthat is desired for a control value, the spring parameters (e.g., K, M,or D) can be tuned to be overdamped or critically damped. After the timet2, when the control value reaches the target value (e.g., at 0.85) forthe shocked expression, the effect of the tunable spring can cause theleft eyebrow to change slightly (up and down) and gradually becomessteady which increases the naturalness of the appearance of an eyebrowraise.

The graph 1650 illustrates a scenario where the weight value within thespring system is adjusted to be heavier than that in the example 1650.For example, the mass of the spring (e.g., the variable M in the formula(4B-i)) associated with the graph 1650 may be larger than that in thegraph 1630). In this example graph 1650, once the value reaches thetarget value of 0.85, the tunable spring can cause the value of thevariable to fluctuate to 1 (as compared to slightly under 1) at time t.Further, in this example, because the mass is bigger for the spring inthe graph 1650, the tunable spring in the graph 1650 can cause the eyebrow to move quickly (e.g., note that the control value remains near 0but then increases more quickly toward the target value than in thegraph 1640) and with greater amplitude. The eyebrow may appear to bounceup and down rather suddenly, which can give an unnatural effect of arubber face as the spring is not tuned properly.

In addition to or as an alternative to solving formulae 4A-4C, thetunable spring system can include a function that represents the linearor oscillatory, damped behavior for face parameters shown in the graphs1630, 1640, 1650. For example, one or more of the parameters of a facevector may be associated with a linear ramp function or a damped,sinusoidal function (e.g., those described with reference to FIG. 16B)which controls the behavior of the parameter. The function can berepresented by a mathematical function, a spline (or otherinterpolating) curve, or a lookup table. The tunable spring system candetermine the movements of the region of the face (associated with theparameter) based on the function. The function may be previously definedand stored, and thus the amount movement of the face may not have to becalculated from the formulae 4A-4C prior to or during rendering, whichmay increase computational efficiency.

In certain implementations, the tunable system can be combined with thetransition mechanisms described with reference to FIGS. 14A-15 toprovide a more realistic animation of the virtual character. Thetransition mechanisms can happen independently of the tunable springsdescribed with reference to FIGS. 16A and 16B. For example, where theface sweeping mechanism is implemented, it may result in a series ofchanges of control values starting at slightly delayed times relative tothe other controls to represent the sweep of an expression across aface. The tunable controls may also take effect for the variables atdifferent times.

Animating A Virtual Character with Realistic Physics and with Sweep

FIG. 17 illustrates an example of changes to a control value of a facevector at different points in time where both the tunable system and thesweeping mechanism are implemented. As shown in the graph 1700, during atransition from a neutral expression to a shocked expression, the lefteye brow change can start at time t1 and the right eye brow may start attime t2 (e.g., due to face sweep). The tunable springs for the lefteyebrow and the right eyebrow can also begin at different times, e.g.,at times t4 and t5 respectively. Other facial regions can be animated atlater times (e.g., forehead wrinkle begins at time t6) as the sweepprogresses, and the corresponding control value of the face vector can(optionally) be associated with its own tunable spring.

Example Processes of Animating A Virtual Character with RealisticPhysics

FIG. 18 illustrates an example process of animating a virtual characterwhich incorporates realistic physical movements. The example process1800 can be performed by the computing device 10, the wearable system200 (e.g., the modules 260, 270 or the avatar processing and renderingsystem 690), alone or in combination. The example process 1800 can beperformed in real time while the virtual character is interacting with auser or an environment.

At block 1810, the process 1800 can detect a trigger for changing from afirst facial expression to a second facial expression. The trigger maybe based on a user's interaction, an event in the environment, etc.

To achieve the second facial expressions, one or more values associatedwith face sliders (e.g., components of a multidimensional face vector)may be updated. At block 1820, the process 1800 can determine a targetvalue of a face slider for the second facial expression. The targetvalue may be a value (e.g., an xyz or angular coordinate value) formoving a 1-D or 2-D face slider. The target value may also be a weightassociated with a set of vertices or a blendshape.

At block 1830, the process 1800 can update the face slider based atleast in part on the target value and a tunable spring system model. Forexample, the value of the face slider can be changed from the valueassociated with the first expression to the target value based on aspring model (e.g., underdamped, overdamped, or critically damped). Thechange to the target value may be gradual to reduce abruptness of thetransition. The transition to the target value may incorporate a tunablesystem for providing realistic physics of the region controlled by theface slider.

At block 1840, a tunable spring can be applied to the face slider inresponse to a determination that the target value is reached. Forexample, the tunable spring can cause the region controlled by the faceslider to oscillate for a short duration after the target value isreached, which may simulate oscillations of the skin or facial muscles.In addition to or in alternative to a tunable spring, other types ofphysical movements can also be applied using similar techniques.Further, the tunable spring (or other types of physics) can be appliedwhen the value of the face slider meets a threshold condition (e.g.,within a range that includes the target value). Different tunable sliderparameters can be applied to different components of the face vector,because different facial regions (e.g., FACS regions) may responddifferently to transitions (e.g., taught skin over skull bone versussofter cheek skin over the mouth cavity).

At block 1850, the process 1800 can cause a display to render ananimation incorporating the tunable spring. For example, the display canrender a visual appearance of the facial transition incorporating theeffects of the tunable slider system (and optionally incorporating theswept transition system). The display can also render the change in theface slider value(s) during a certain period of time (e.g., an eyebrowraise over several milliseconds, etc.).

Overview of a Computing Device

FIG. 19 illustrates an example computing device 10 for implementingvarious techniques associated with animating or rendering a virtualcharacter. For example, the computing device 10 can implement varioustechniques described with reference to FIGS. 11-18. Other variations ofthe computing device 10 may be substituted for the examples explicitlypresented herein, such as removing or adding components to the computingdevice 10. The computing device 10 may include a game device, a smartphone, a tablet, a personal computer, a laptop, a smart television, acar console display, a server, and the like. The computing device 10 mayalso be distributed across multiple geographical locations. For example,the computing device 10 may be a cluster of cloud-based servers.

As shown, the computing device 10 includes a processing unit 20 thatinteracts with other components of the computing device 10 and alsoexternal components to computing device 10. A virtual application mediareader 22 is included that communicates with a virtual application media12 (which may include one or more virtual characters, such as, e.g., thevirtual avatar described herein). The game media reader 22 may be anoptical disc reader capable of reading optical discs, such as CD-ROMs orDVDs, or any other type of reader that can receive and read data fromgame media 12. One or more of the computing devices may be used toimplement one or more of the systems disclosed herein.

Computing device 10 may include a separate graphics processor 24. Insome cases, the graphics processor 24 may be built into the processingunit 20. In some such cases, the graphics processor 24 may share RandomAccess Memory (RAM) with the processing unit 20. Alternatively oradditionally, the computing device 10 may include a discrete graphicsprocessor 24 that is separate from the processing unit 20. In some suchcases, the graphics processor 24 may have separate RAM from theprocessing unit 20. Computing device 10 might be a handheld gameapplication device, a dedicated game console computing system, ageneral-purpose laptop or desktop computer, a smart phone, a tablet, acar console, or other suitable system.

Computing device 10 also includes various components for enablinginput/output, such as an I/O 32, a user I/O 34, a display I/O 36, and anetwork I/O 38. I/O 32 interacts with storage element 40 and, through adevice 42, removable storage media 44 in order to provide storage forcomputing device 10. Processing unit 20 can communicate through I/O 32to store data, such as game state data and any shared data files. Inaddition to storage 40 and removable storage media 44, computing device10 is also shown including ROM (Read-Only Memory) 46 and RAM 48. RAM 48may be used for data that is accessed frequently, such as when a videogame is being played.

User I/O 34 is used to send and receive commands between processing unit20 and user devices, such as game controllers. In some embodiments, theuser I/O 34 can include a touchscreen input. The touchscreen can becapacitive touchscreen, a resistive touchscreen, or other type oftouchscreen technology that is configured to receive user input throughtactile inputs from the player. Display I/O 36 provides input/outputfunctions that are used to display images from the game being played.Network I/O 38 is used for input/output functions for a network. NetworkI/O 38 may be used during execution of a game, such as when a game isbeing played online or being accessed online, application of frauddetection, and/or generation of a fraud detection model.

Display output signals produced by display I/O 36 comprise signals fordisplaying visual content produced by computing device 10 on a displaydevice, such as graphics, user interfaces, video, and/or other visualcontent. Computing device 10 may comprise one or more integrateddisplays configured to receive display output signals produced bydisplay I/O 36. According to some embodiments, display output signalsproduced by display I/O 36 may also be output to one or more displaydevices external to computing device 10.

The computing device 10 can also include other features that may be usedwith a video game, such as a clock 50, flash memory 52, and othercomponents. An audio/video player 56 might also be used to play a videosequence, such as a movie. It should be understood that other componentsmay be provided in computing device 10 and that a person skilled in theart will appreciate other variations of computing device 10.

Program code can be stored in ROM 46, RAM 48 or storage 40 (which mightcomprise a hard disk, other magnetic storage, optical storage, othernon-volatile storage or a combination or variation of these). Part ofthe program code can be stored in ROM that is programmable (ROM, PROM,EPROM, EEPROM, and so forth), and part of the program code can be storedin storage 40, and/or on removable media such as game media 12 (whichcan be a CD-ROM, cartridge, memory chip or the like, or obtained over anetwork or other electronic channel as needed). In general, program codecan be found embodied in a tangible non-transitory signal-bearingmedium.

Random access memory (RAM) 48 (and possibly other storage) is usable tostore variables and other game and processor data as needed. RAM 48 isused and holds data that is generated during the execution of anapplication and portions thereof might also be reserved for framebuffers, application state information, and/or other data needed orusable for interpreting user input and generating display outputs.Generally, RAM 48 is volatile storage and data stored within RAM 48 maybe lost when the computing device 10 is turned off or loses power.

As computing device 10 reads virtual application media 12 and providesan application, information may be read from game media 12 and stored ina memory device, such as RAM 48. Additionally, data from storage 40, ROM46, servers accessed via a network (not shown), or removable storagemedia 44 may be read and loaded into RAM 48. Although data is describedas being found in RAM 48, it will be understood that data does not haveto be stored in RAM 48 and may be stored in other memory accessible toprocessing unit 20 or distributed among several media, such as a virtualapplication media 12 and storage 40.

Additional Aspects

In a 1st aspect, a system for generating a map of facial expressions,the system comprising: non-transitory storage medium storing vectorvalues for facial expressions; and a hardware processor programmed to:identify a set of facial expressions and a neutral expression to beprojected onto a map, wherein each facial expression is represented byan expression specific vector and the neutral expression is representedby a neutral vector; calculate a first expression specific delta vectorof a first facial expression based on the first expression specificvector and the neutral vector; calculate a first length of the firstexpression specific delta vector; calculate a second expression specificdelta vector of a second facial expression based on the secondexpression specific vector and the neutral vector; calculate a secondlength for the second expression specific delta vector; calculate anangular relationship between the first expression specific delta vectorand the second expression specific delta vector; and project the firstfacial expression and the second facial expression onto a map, whereinlocations of the first facial expression and second facial expression,respectively, with reference to the neutral expression are determinedbased at least in part on the first length and the second length, andwherein a relative position between the first facial expression and thesecond facial expression is determined based at least in part on theangular relationship between the first expression specific delta vectorand the second expression specific delta vector.

In a 2nd aspect, the system of aspect 1, wherein the map comprisestwo-dimensional projections of the set of facial expressions.

In a 3rd aspect, the system of any one of aspects 1-2, wherein the mapcomprises a plurality of arms with each arm being positioned with one ormore expressions, and each arm of the plurality of arms is connected tothe neutral expression.

In a 4th aspect, the system of aspect 3, wherein the map iswheel-shaped, such that the neutral expression is placed at the centerof the wheel-shaped map.

In a 5th aspect, the system of aspect 4, wherein two expressions on anarm have two expression specific delta vectors whose angularrelationship corresponds to an angle less than 10 degrees.

In a 6th aspect, the system of aspect 5, wherein the two expressionspecific delta vectors correspond to two similar expressions withdifferent intensities.

In a 7th aspect, the system of any one of aspects 1-6, wherein theexpression specific vector comprises a plurality of dimensions, whereeach dimension is usable to drive deformations of a region of a mesh ofa virtual character's face.

In an 8th aspect, the system of claim 7, wherein the expression specificvector comprises over 100 dimensions.

In a 9th aspect, the system of any one of aspects 1-8, wherein one ormore of following are unitized: the first expression specific vector,the second expression specific vector, the first expression specificdelta vector, the second expression specific delta vector.

In a 10th aspect, the system of any one of aspects 1-9, wherein thehardware processor is programmed to: determine a position of ananimation blend cursor; identify a plurality of facial expressionsaround the blend cursor wherein the plurality of facial expressionsforms a polygon; determine weights corresponding to the plurality facialexpressions based at least in part on the position of the animationblend cursor with respective to locations of the plurality facialexpressions on the map; generate an animation of a facial expressionoutside of the set of facial expressions projected onto the map based onthe plurality facial expressions and the weights corresponding to thethree facial expressions.

In an 11th aspect, the system of any one of aspects 1-10, wherein thehardware processor is further programmed to: calculate delta vectors forvectors other than the first and second vectors in the set of vectorscorresponding to the set of facial expressions; calculate angularrelationships between the first expression specific delta vector and thedelta vectors for the vectors other than the first and second vectorscorresponding to the set of facial expressions; and output the mapcomprising the set of facial expressions wherein positions of eachfacial expression are determined based at least in part on the angularrelationships and the delta vectors.

In a 12th aspect, the system of any one of aspects 1-11, wherein: tocalculate a first expression specific delta vector, the hardwareprocessor is programmed to subtract the neutral vector from the firstexpression specific vector.

In a 13th aspect, the system of any one of aspects 1-12, wherein tocalculate the angular relationship between the first expression specificdelta vector and the second expression specific delta vector, thehardware processor is programmed to calculate a dot product between thefirst expression specific delta vector and the second expressionspecific delta vector.

In a 14th aspect, a method for generating a map of facial expressions,the method comprising: identifying a set of facial expressions to beprojected onto a map, wherein each facial expression is represented byan expression specific vector; taking a difference between a firstexpression specific vector of a first facial expression and a referencevector to generate a first expression specific delta vector; takinganother difference between a second expression specific vector of asecond facial expression and the reference vector to generate a secondexpression specific delta vector; determining a dot product between thefirst expression specific delta vector and the second expressionspecific delta vector; and project the first facial expression and thesecond facial expression onto a map, wherein a relative position betweenthe first facial expression and the second facial expression isdetermined based at least in part on the dot product between the firstexpression specific delta vector and the second expression specificdelta vector.

In a 15th aspect, the method of aspect 14, wherein the reference vectorrepresents a neutral expression.

In a 16th aspect, the method of aspect 14 or 15, wherein the mapcomprises two-dimensional projections of the set of facial expressions.

In a 17th aspect, the method of any one of aspects 14-16, wherein themap has a plurality of arms with each arm being positioned with one ormore expressions, and each arm of the plurality of arms is connected toan expression associated with the reference vector.

In an 18th aspect, the method of aspect 17, wherein an expressionassociated with the reference vector is placed at the center of a wheelshaped map.

In a 19th aspect, the method of aspect 18, wherein distances between thefirst expression and second expression with respect to the center of thewheel shaped map are determined based on lengths of the first expressionspecific delta vector and the second expression specific delta vector,respectively.

In a 20th aspect, the method of aspect 18 or 19, wherein two expressionson an arm have two expression specific delta vectors whose dot productapproximately equals to 1.

In a 21st aspect, the method of aspect 20, wherein the two expressionspecific delta vectors correspond to two similar expressions withdifferent intensities, wherein the expression with higher intensity isplaced farther away from the center of the wheel shaped map.

In a 22nd aspect, the method of any one of aspects 18-21, wherein twoexpressions on an opposite side of the wheel shaped map have a dotproduct approximately equal to −1.

In a 23rd aspect, the method of any one of aspects 14-22, wherein theexpression specific vector comprises a plurality of dimensions, whereeach dimension drives deformations of a region of a mesh of a virtualcharacter's face.

In a 24th aspect, the method of aspect 23, wherein the expressionspecific vector comprises 137 dimensions.

In a 25th aspect, the method of any one of aspects 14-24, wherein one ormore of following are unitized: the first expression specific vector,the second expression specific vector, the first expression specificdelta vector, the second expression specific delta vector.

In a 26th aspect, the method of aspect 25, unitizing a vector comprises:calculating a vector length; and for a value in each dimension of thevector, dividing the value by the vector to generate a unitized vector.

In a 27th aspect, the method of any one of aspects 14-26, wherein themap is applied as part of animation blendspace to create additionalfacial expressions outside of the map.

In a 28th aspect, a system for transitioning a first expression to asecond expression for a virtual character, the system comprising:non-transitory storage medium storing vector values for facialexpressions of a virtual character; and a hardware processor programmedto: detect a first trigger of an expression change from a firstexpression to a second expression; in response to the first trigger,determine first values of parameters of a transition system, wherein theparameters comprise a starting facial expression, an ending facialexpression, and a sweep direction; determine a first starting facialexpression and a first ending facial expression for a first time periodduring the transition from the first expression to the second expressionbased at least in part on the first values of the parameters of thetransition system; update the vector values for changing the virtualcharacter's facial expression from the first starting facial expressionand the first ending facial expression at the first time period; detecta second trigger of another expression change from the second expressionto the third expression; in response to the second trigger, determinesecond values of the parameters of the transition system; determine asecond starting facial expression and a second ending facial expressionfor a second time period based at least in part on the first values andthe second values of the parameters of the transition systems; updatethe vector values for changing the virtual character's facial expressionfrom the second starting facial expression to the second ending facialexpression at the second time period.

In a 29th aspect, the system of aspect 28, wherein at least one of thefirst trigger or the second trigger is caused by: an interaction of auser with the virtual character or an event in an environment of thevirtual character.

In a 30th aspect, the system of aspect 28 or 29, wherein the second timeperiod occurs during the transition between the first expression to thesecond expression.

In a 31st aspect, the system of aspect 30, wherein the second endingfacial expression comprises a first portion of the face having a firstexpression associated with the second expression and a second portion ofthe face having a second expression associated with the thirdexpression.

In a 32nd aspect, the system of aspect 31, wherein the hardwareprocessor is further programmed to calculate a rate of change ofexpressions, and wherein the second ending facial expression comprisesthe first and the second expressions in response to a determination thatthe rate of change of expressions is faster than a sweep speedassociated with transitioning from the first expression to the secondexpression.

In a 33rd aspect, the system of any one of aspects 28-32, wherein facialexpression of the virtual character's face is controlled by a facevector comprising a plurality of dimensions with each vector valuecorresponding to a dimension of the plurality of dimensions.

In a 34th aspect, the system of any one of aspects 28-33, wherein thesecond starting facial expression is the same as the first ending facialexpression.

In a 35th aspect, the system of any one of aspects 28-34, wherein thefirst expression is the same as the third expression.

In a 36th aspect, the system of any one of aspects 28-35, wherein afirst sweeping direction value in the first values for transitioningfrom the first expression to the second expression is different from asecond sweeping direction values in the second values for transitioningfrom the second expression to the third expression.

In a 37th aspect, the system of aspect 36, wherein the first sweepingdirection is applied to determine the second starting facial expressionand the second ending facial expression for the second time period fortransitioning between the second and third expressions in response to adetermination that at least a portion of the face still has anexpression associated with the first expression.

In a 38th aspect, the system of aspect 36 or 37, wherein the secondsweeping direction is applied to determine the second starting facialexpression and the second ending facial expression for the second timeperiod for transitioning between the second and third expressions inresponse to a determination that a transition from the first expressionto the second expression has been completed prior to the second timeperiod.

In a 39th aspect, the system of any one of aspects 28-38, wherein thesweep direction is randomized for each transition.

In a 40th aspect, the system of any one of aspects 28-39, wherein atleast one of the first, second, or third expression can be determinedfrom a wheel shaped map comprising a set of expressions projected on toa plurality of arms of the wheel shaped map wherein similar expressionsare located in the same directions on the wheel shaped map.

In a 41st aspect, the system of aspect 40, wherein a movement from thefirst expression to the second expression and then to the thirdexpression is associated with an expression change trajectory on thewheel shaped map.

In a 42nd aspect, a method for transitioning a first expression to asecond expression for a virtual character, the method comprising: undercontrol of a hardware processor: detecting a first trigger of anexpression change from a first expression to a second expression; inresponse to the first trigger, determining a first starting facialexpression and a first ending facial expression for a first time periodduring a transition from the first expression to the second expression;updating vector values of a face vector for changing a virtualcharacter's facial expression from the first starting facial expressionand the first ending facial expression at the first time period;detecting a second trigger of another expression change from the secondexpression to the third expression; in response to the second trigger,determining a second starting facial expression and a second endingfacial expression for a second time period to transition to the thirdexpression; updating the vector values for changing the virtualcharacter's facial expression from the second starting facial expressionto the second ending facial expression at the second time period,wherein the second time period occurs during the transition between thefirst expression to the second expression.

In a 43rd aspect, the method of aspect 42, wherein at least one of thefirst trigger or the second trigger is caused by: an interaction of auser with the virtual character or an event in an environment of thevirtual character.

In a 44th aspect, the method of aspect 42 or 43, wherein the secondending facial expression comprises a first portion of the face having afirst expression associated with the second expression and a secondportion of the face having a second expression associated with the thirdexpression.

In a 45th aspect, the method of aspect 44, the second ending facialexpression comprises the first and the second expressions in response toa determination that a rate of change of expressions is faster than asweep speed associated with transitioning from the first expression tothe second expression.

In a 46th aspect, the method of any one of aspects 42-45, wherein facialexpression of the virtual character's face is controlled by a facevector comprising a plurality of dimensions with each vector valuecorresponding to a dimension of the plurality of dimensions.

In a 47th aspect, the method of any one of aspects 42-46, wherein thesecond starting facial expression is the same as the first ending facialexpression.

In a 48th aspect, the method of any one of aspects 42-47, wherein thefirst expression is the same as the third expression.

In a 49th aspect, the method of any one of aspects 42-48, wherein afirst sweeping direction value for transitioning from the firstexpression to the second expression is different from a second sweepingdirection values for transitioning from the second expression to thethird expression.

In a 50th aspect, the method of aspect 49, further comprising disablingthe second sweeping direction associated with a transition from thesecond expression to the third expression.

In a 51st aspect, the method of aspect 49 or 50, wherein the sweepdirection is randomized for each transition.

In a 52nd aspect, the method of any one of aspects 42-51, wherein atleast one of the first, second, or third expression can be determinedfrom a wheel shaped map comprising a set of expressions projected on toa plurality of arms of the wheel shaped map wherein similar expressionsare located in the same directions on the wheel shaped map.

In a 53rd aspect, a method for transitioning expressions for a virtualcharacter, the method comprising: under control of a hardware processor:identifying a first trigger of a first expression change from a firstexpression to a second expression for a virtual character; determiningparameters of the first expression change; sweeping the secondexpression across the face of the virtual character based at least inpart on the parameters; identifying a second trigger of a secondexpression change from the second expression to a third expression,wherein the second trigger occurs prior to the first expression changecompletes; and initiating sweeping of the third expression across theface while continue to sweep the second expression across the face.

In a 54th aspect, the method of aspect 53, wherein initiating sweepingof the third expression across the face while continue to sweep thesecond expression across the face comprises: changing a first region ofthe face from the second expression to the third expression; andchanging a second region of the face from the first expression to thesecond expression.

In a 55th aspect, the method of aspect 53 or 54, wherein the parameterscomprise at least one of a sweeping speed or a sweeping direction.

In a 56th aspect, a system for animating a virtual character, the systemcomprising: non-transitory storage medium storing control systems forfacial expressions of a virtual character, wherein the control systemscomprise a plurality of face sliders implemented with tunable springs; adisplay for rendering the virtual character; and a hardware processorprogrammed to: detect a trigger for changing the virtual character'sfacial expression from a first facial expression to a second facialexpression; determine one or more of the face sliders to be updated inresponse to the trigger; determine a target value of a face slider ofthe one or more face sliders; update a value of the face slider to thetarget value; apply a tunable spring to the face slider in response to adetermination that the target value is reached; and cause the display torender the virtual character to show a change from the first facialexpression to the second facial expression with the tunable spring.

In a 57th aspect, the system of aspect 56, wherein to update the valueof the face slider to the target value, the hardware processor isfurther programmed to apply a tunable control associated with thetunable spring to gradually update the value of the face slider to thetarget value.

In a 58th aspect, the system of aspect 56 or 57, wherein the face slidercontrols one or more vertices of a mesh of the virtual character.

In a 59th aspect, the system of any one of aspects 56-58, wherein thetunable spring causes a cyclic motion to be performed on a regioncontrolled by the face slider.

In a 60th aspect, the system of any one of aspects 56-59, wherein thetunable spring represents an underdamped oscillation asymptotic to thetarget value.

In a 61st aspect, the system of any one of aspects 56-60, wherein thecontrol system further comprises a sweeping mechanism for changing thefacial expression, and the sweeping mechanism causes the tunable springto the face slider to occur at a different time than another tunablespring to another face slider.

In a 62nd aspect, a method for animating a virtual character, the methodcomprising: detecting a trigger for changing a virtual character'sfacial expression from a first facial expression to a second facialexpression; determining one or more of face sliders of a control systemof the virtual character to be updated in response to the trigger;determining a target value of a face slider of the one or more facesliders, wherein the face slider comprises a physicality implemented tosimulate real world physical movements; updating a value of the faceslider to the target value; activating a physicality for the face sliderin response to a determination that a threshold condition is reached;and causing the display to render the virtual character to show a changefrom the first facial expression to the second facial expression withthe physicality.

In a 63rd aspect, the method of aspect 62, wherein the physicalitycomprises a tunable spring which causes cyclic motion to be performed ona region controlled by the face slider.

In a 64th aspect, the method of aspect 62 or 63, wherein the face slidercontrols one or more vertices of a mesh of the virtual character.

In a 65th aspect, the method of any one of aspects 62-64, wherein thethreshold condition comprises a threshold value below the target value.

In a 66th aspect, the method of any one of aspects 62-65, wherein thecontrol system further comprises a sweeping mechanism for changing thefacial expression, and the sweeping mechanism causes the physicality tothe face slider to occur at a different time than physicality to anotherface slider.

OTHER CONSIDERATIONS

Each of the processes, methods, and algorithms described herein and/ordepicted in the attached figures may be embodied in, and fully orpartially automated by, code modules executed by one or more physicalcomputing systems, hardware computer processors, application-specificcircuitry, and/or electronic hardware configured to execute specific andparticular computer instructions. For example, computing systems caninclude general purpose computers (e.g., servers) programmed withspecific computer instructions or special purpose computers, specialpurpose circuitry, and so forth. A code module may be compiled andlinked into an executable program, installed in a dynamic link library,or may be written in an interpreted programming language. In someimplementations, particular operations and methods may be performed bycircuitry that is specific to a given function.

Further, certain implementations of the functionality of the presentdisclosure are sufficiently mathematically, computationally, ortechnically complex that application-specific hardware or one or morephysical computing devices (utilizing appropriate specialized executableinstructions) may be necessary to perform the functionality, forexample, due to the volume or complexity of the calculations involved orto provide results substantially in real-time. For example, animationsor video may include many frames, with each frame having millions ofpixels, and specifically programmed computer hardware is necessary toprocess the video data to provide a desired image processing task orapplication in a commercially reasonable amount of time. As describedabove, the volume of the multidimensional facial expression space may beso enormously large that a rule-based approach must be computationallyimplemented on computer hardware, particularly to render virtual avatarfacial expressions in real-time in an augmented, virtual, or mixedreality environment.

Code modules or any type of data may be stored on any type ofnon-transitory computer-readable medium, such as physical computerstorage including hard drives, solid state memory, random access memory(RAM), read only memory (ROM), optical disc, volatile or non-volatilestorage, combinations of the same and/or the like. The methods andmodules (or data) may also be transmitted as generated data signals(e.g., as part of a carrier wave or other analog or digital propagatedsignal) on a variety of computer-readable transmission mediums,including wireless-based and wired/cable-based mediums, and may take avariety of forms (e.g., as part of a single or multiplexed analogsignal, or as multiple discrete digital packets or frames). The resultsof the disclosed processes or process steps may be stored, persistentlyor otherwise, in any type of non-transitory, tangible computer storageor may be communicated via a computer-readable transmission medium.

Any processes, blocks, states, steps, or functionalities in flowdiagrams described herein and/or depicted in the attached figures shouldbe understood as potentially representing code modules, segments, orportions of code which include one or more executable instructions forimplementing specific functions (e.g., logical or arithmetical) or stepsin the process. The various processes, blocks, states, steps, orfunctionalities can be combined, rearranged, added to, deleted from,modified, or otherwise changed from the illustrative examples providedherein. In some embodiments, additional or different computing systemsor code modules may perform some or all of the functionalities describedherein. The methods and processes described herein are also not limitedto any particular sequence, and the blocks, steps, or states relatingthereto can be performed in other sequences that are appropriate, forexample, in serial, in parallel, or in some other manner. Tasks orevents may be added to or removed from the disclosed exampleembodiments. Moreover, the separation of various system components inthe implementations described herein is for illustrative purposes andshould not be understood as requiring such separation in allimplementations. It should be understood that the described programcomponents, methods, and systems can generally be integrated together ina single computer product or packaged into multiple computer products.Many implementation variations are possible.

The processes, methods, and systems may be implemented in a network (ordistributed) computing environment. Network environments includeenterprise-wide computer networks, intranets, local area networks (LAN),wide area networks (WAN), personal area networks (PAN), cloud computingnetworks, crowd-sourced computing networks, the Internet, and the WorldWide Web. The network may be a wired or a wireless network or any othertype of communication network.

The systems and methods of the disclosure each have several innovativeaspects, no single one of which is solely responsible or required forthe desirable attributes disclosed herein. The various features andprocesses described above may be used independently of one another, ormay be combined in various ways. All possible combinations andsubcombinations are intended to fall within the scope of thisdisclosure. Various modifications to the implementations described inthis disclosure may be readily apparent to those skilled in the art, andthe generic principles defined herein may be applied to otherimplementations without departing from the spirit or scope of thisdisclosure. Thus, the claims are not intended to be limited to theimplementations shown herein, but are to be accorded the widest scopeconsistent with this disclosure, the principles and the novel featuresdisclosed herein.

Certain features that are described in this specification in the contextof separate implementations also can be implemented in combination in asingle implementation. Conversely, various features that are describedin the context of a single implementation also can be implemented inmultiple implementations separately or in any suitable subcombination.Moreover, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination. No single feature orgroup of features is necessary or indispensable to each and everyembodiment.

Conditional language used herein, such as, among others, “can,” “could,”“might,” “may,” “e.g.,” and the like, unless specifically statedotherwise, or otherwise understood within the context as used, isgenerally intended to convey that certain embodiments include, whileother embodiments do not include, certain features, elements and/orsteps. Thus, such conditional language is not generally intended toimply that features, elements and/or steps are in any way required forone or more embodiments or that one or more embodiments necessarilyinclude logic for deciding, with or without author input or prompting,whether these features, elements and/or steps are included or are to beperformed in any particular embodiment. The terms “comprising,”“including,” “having,” and the like are synonymous and are usedinclusively, in an open-ended fashion, and do not exclude additionalelements, features, acts, operations, and so forth. Also, the term “or”is used in its inclusive sense (and not in its exclusive sense) so thatwhen used, for example, to connect a list of elements, the term “or”means one, some, or all of the elements in the list. In addition, thearticles “a,” “an,” and “the” as used in this application and theappended claims are to be construed to mean “one or more” or “at leastone” unless specified otherwise.

As used herein, a phrase referring to “at least one of” a list of itemsrefers to any combination of those items, including single members. Asan example, “at least one of: A, B, or C” is intended to cover: A, B, C,A and B, A and C, B and C, and A, B, and C. Conjunctive language such asthe phrase “at least one of X, Y and Z,” unless specifically statedotherwise, is otherwise understood with the context as used in generalto convey that an item, term, etc. may be at least one of X, Y or Z.Thus, such conjunctive language is not generally intended to imply thatcertain embodiments require at least one of X, at least one of Y and atleast one of Z to each be present.

Similarly, while operations may be depicted in the drawings in aparticular order, it is to be recognized that such operations need notbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Further, the drawings may schematically depict one more exampleprocesses in the form of a flowchart. However, other operations that arenot depicted can be incorporated in the example methods and processesthat are schematically illustrated. For example, one or more additionaloperations can be performed before, after, simultaneously, or betweenany of the illustrated operations. Additionally, the operations may berearranged or reordered in other implementations. In certaincircumstances, multitasking and parallel processing may be advantageous.Moreover, the separation of various system components in theimplementations described above should not be understood as requiringsuch separation in all implementations, and it should be understood thatthe described program components and systems can generally be integratedtogether in a single software product or packaged into multiple softwareproducts. Additionally, other implementations are within the scope ofthe following claims. In some cases, the actions recited in the claimscan be performed in a different order and still achieve desirableresults.

What is claimed is:
 1. A system for transitioning a first expression toa second expression for a virtual character, the system comprising:non-transitory storage medium storing vector values for facialexpressions of a virtual character; and a hardware processor programmedto: detect a first trigger of an expression change from a firstexpression to a second expression; in response to the first trigger,determine first values of parameters of a transition system, wherein theparameters comprise a starting facial expression, an ending facialexpression, and a sweep direction; determine a first starting facialexpression and a first ending facial expression for a first time periodduring the transition from the first expression to the second expressionbased at least in part on the first values of the parameters of thetransition system; update the vector values for changing the virtualcharacter's facial expression from the first starting facial expressionand the first ending facial expression at the first time period; detecta second trigger of another expression change from the second expressionto a third expression; in response to the second trigger, determinesecond values of the parameters of the transition system; determine asecond starting facial expression and a second ending facial expressionfor a second time period based at least in part on the first values andthe second values of the parameters of the transition systems; andupdate the vector values for changing the virtual character's facialexpression from the second starting facial expression to the secondending facial expression at the second time period.
 2. The system ofclaim 1, wherein at least one of the first trigger or the second triggeris caused by: an interaction of a user with the virtual character or anevent in an environment of the virtual character.
 3. The system of claim1, wherein the second time period occurs during the transition betweenthe first expression to the second expression.
 4. The system of claim 3,wherein the second ending facial expression comprises a first portion ofthe face having a first expression associated with the second expressionand a second portion of the face having a second expression associatedwith the third expression.
 5. The system of claim 4, wherein thehardware processor is further programmed to calculate a rate of changeof expressions, and wherein the second ending facial expressioncomprises the first and the second expressions in response to adetermination that the rate of change of expressions is faster than asweep speed associated with transitioning from the first expression tothe second expression.
 6. The system of claim 1, wherein facialexpression of the virtual character's face is controlled by a facevector comprising a plurality of dimensions with each vector valuecorresponding to a dimension of the plurality of dimensions.
 7. Thesystem of claim 1, wherein the second starting facial expression is thesame as the first ending facial expression.
 8. The system of claim 1,wherein at least one of the first, second, or third expression can bedetermined from a wheel shaped map comprising a set of expressionsprojected on to a plurality of arms of the wheel shaped map whereinsimilar expressions are located in the same directions on the wheelshaped map.
 9. The system of claim 8, wherein a movement from the firstexpression to the second expression and then to the third expression isassociated with an expression change trajectory on the wheel shaped map.10. A method for transitioning a first expression to a second expressionfor a virtual character, the method comprising: under control of ahardware processor: detecting a first trigger of an expression changefrom a first expression to a second expression; in response to the firsttrigger, determining a first starting facial expression and a firstending facial expression for a first time period during a transitionfrom the first expression to the second expression; updating vectorvalues of a face vector for changing a virtual character's facialexpression from the first starting facial expression and the firstending facial expression at the first time period; detecting a secondtrigger of another expression change from the second expression to athird expression; in response to the second trigger, determining asecond starting facial expression and a second ending facial expressionfor a second time period to transition to the third expression; andupdating the vector values for changing the virtual character's facialexpression from the second starting facial expression to the secondending facial expression at the second time period, wherein the secondtime period occurs during the transition between the first expression tothe second expression.
 11. The method of claim 10, wherein at least oneof the first trigger or the second trigger is caused by: an interactionof a user with the virtual character or an event in an environment ofthe virtual character.
 12. The method of claim 10, wherein the secondending facial expression comprises a first portion of the face having afirst expression associated with the second expression and a secondportion of the face having a second expression associated with the thirdexpression.
 13. The method of claim 12, the second ending facialexpression comprises the first and the second expressions in response toa determination that a rate of change of expressions is faster than asweep speed associated with transitioning from the first expression tothe second expression.
 14. The method of claim 10, wherein facialexpression of the virtual character's face is controlled by a facevector comprising a plurality of dimensions with each vector valuecorresponding to a dimension of the plurality of dimensions.
 15. Themethod of claim 10, wherein the second starting facial expression is thesame as the first ending facial expression.
 16. The method of claim 10,wherein the first expression is the same as the third expression. 17.The method of claim 10, wherein at least one of the first, second, orthird expression can be determined from a wheel shaped map comprising aset of expressions projected on to a plurality of arms of the wheelshaped map wherein similar expressions are located in the samedirections on the wheel shaped map.
 18. A method for transitioningexpressions for a virtual character, the method comprising: undercontrol of a hardware processor: identifying a first trigger of a firstexpression change from a first expression to a second expression for avirtual character; determining parameters of the first expressionchange; sweeping the second expression across the face of the virtualcharacter based at least in part on the parameters; identifying a secondtrigger of a second expression change from the second expression to athird expression, wherein the second trigger occurs prior to the firstexpression change completes; and initiating sweeping of the thirdexpression across the face while continue to sweep the second expressionacross the face.
 19. The method of claim 18, wherein initiating sweepingof the third expression across the face while continuing to sweep thesecond expression across the face comprises: changing a first region ofthe face from the second expression to the third expression; andchanging a second region of the face from the first expression to thesecond expression.
 20. The method of claim 18, wherein the parameterscomprise at least one of a sweeping speed or a sweeping direction.